KR20110050475A - System, method and program for making composition plan and allocation of ships - Google Patents

Abstract

This system includes a wiring plan for transporting a blended raw material of a plurality of items from a plurality of shipping destinations to a plurality of landing places, and a blending and wiring plan for creating a mixing plan for mixing the received raw materials at each landing site. It is a creation system, Comprising: The 1st formulation plan preparation part which creates a 1st formulation plan based on the acquisition target amount of the said compounding raw material preset for every said shipment place and for each said item, and said wiring plan based on the created said 1st formulation plan. A wiring plan preparation unit to create and a database unit for storing the created wiring plan are provided.

Description

SYSTEM, METHOD AND PROGRAM FOR MAKING COMPOSITION PLAN AND ALLOCATION OF SHIPS

The present invention provides a blending scheme for receiving and mixing a plurality of blended raw materials (hereinafter, simply referred to as raw materials), and for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites. It relates to formulation and wiring planning systems, methods, and programs suitable for planning.

This application claims priority based on Japanese Patent Application No. 2008-298596 for which it applied to Japan on November 21, 2008, and uses the content here.

In many industries including steel, various kinds of raw materials having various properties purchased according to a contracted purchase target amount are mixed, and products and semi-finished products such as steel are manufactured using the raw materials after the mixing. At this time, the transportation plan (called a wiring plan in the case of ships) and the compounding plan are carried out so as to satisfy the production volume while keeping the properties of products such as steel and semi-finished products within a certain range, and to prevent stocks of each raw material from occurring at the manufacturing site. It is required to build up. And in preparing a wiring plan and a compounding plan, it is judged that the plan is good or bad with cost as an important index. This requires minimizing the cost of transportation (freight, which is the cost of using ships, and the fee for paying when a vessel is anchored at the port for more than the contract term) and the cost of purchasing raw materials.

However, if the wiring plan of the ship to unload (receive) the raw material is not determined, the item and quantity of the raw material to be unloaded in the port is not determined. As a result, in an ironworks where the raw materials are unloaded, it is impossible to determine which items can be used and in what amount, that is, a formulation plan cannot be prepared. On the other hand, in order to prepare the wiring plan of a ship, it is necessary to determine which quantity and how much quantity to use at the steelworks which are the two ports which take off raw materials. As described above, since the compounding plan and the wiring plan are deeply correlated with each other, it is very difficult to plan either one independently.

As a related art, in the inference apparatus for raw material transport wiring plan disclosed in patent document 1, after reading the usage plan of raw material and the annual operation plan of raw material ship as known data, the item which is likely to cause a stock shortage is given priority. Engage with the ship. By repeating this process, a wiring plan is created.

In addition, in the logistics plan preparation device disclosed in Patent Document 2, the simulation section simulates the operation of each transport means based on the constraint conditions, and the stock inventory change calculation section calculates the change of the stock quantity for each raw material item based on the simulation result. Calculate. The result of this calculation is evaluated in an evaluation value calculation part.

Japanese Patent Application Laid-open No. Hei 8-272402 Japanese Patent Application Laid-open No. Hei 11-310313

However, both Patent Document 1 and Patent Document 2 read a plan of use of raw materials and an annual operation plan of a raw material line as known data to create a wiring plan. In other words, it is not considered to create a combination plan and a wiring plan in conjunction with each other.

In the actual transportation, ships operated on the basis of other types of charter party contracts, for example, continuous sailing ships, irregular ships and spot ships, are used. However, in Patent Documents 1 and 2, such ships are used. Minimization of transport costs, including the type of car, is not considered.

In contracts such as continuous sailing vessels and irregular vessels, it is necessary to wire the target vessel (first priority). On the other hand, the spot line needs to determine the size of the ship and the number of ships to be used appropriately according to the target amount of acquisition and the stock situation. However, Patent Documents 1 and 2 do not minimize the transportation cost in consideration of the tip configuration of the ship in consideration of such charter party type. That is, for example, whether it is good to wire with one continuous sailing line and two spot lines with a maximum load of 75000 tons (ton, t), or with one continuous sailing line and three spot lines with a maximum load of 50000 tons The method of wiring plan which considered the option of whether it is good or not is necessary in actual work. Although the transportation cost of a ship changes with the maximum loading amount of a ship to be used, and the route, the wiring which considered these is not performed in the said document.

In addition, when a plan is prepared without considering the transport cost in the blending plan, there is a fear that a blending plan using raw materials having a higher transport cost than necessary is created. In the case of this planning method, it is difficult to optimize the transportation cost no matter how the transportation is devised after the formulation planning decision. For example, consider the case where there are raw materials X and Y having almost the same properties, and in both ports (steelworks) A and B, the use of either of the raw materials X and Y is possible. The cost of transporting raw material X to port A is 20 $ / ton, the cost of transporting raw material Y is 40 $ / ton, the cost of transporting raw material X to port B is 40 $ / ton, and the cost of transporting raw material Y 20 $ / Let's say tone. In this case, it is more advantageous to plan to use the raw material X in both ports A and the raw material Y in both ports B in terms of transportation costs. However, if a planning method is used that does not take transport costs into account, there is a concern that a plan may be prepared to use raw material Y in port A and raw material X in port B.

In addition, in actual operation, when the stock situation of the item to be used is strict, the item whose properties are close to (the item contained in the range in which the property is prescribed; the item which has a certain chemical property in common; the item which can be used even if mutually substituted) By using as a substitute, the stock shortage is suppressed. In addition, by actively using this alternative, instead of items that can only be transported by ships with high rates, arrangements can be made to ships with lower rates with items of nearer properties (items included in the prescribed range). By transporting an existing item, the transportation cost is reduced.

Thus, when cost is considered, it is required to prepare a plan in consideration of the transportation cost as well as the purchase cost of a blended raw material. However, both Patent Literature 1 and Patent Literature 2 do not consider up to the above circumstances in the stage of plan for using raw materials.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, in which a combination plan for receiving and mixing a plurality of items of blended raw materials and a wiring plan for transporting a plurality of items of raw materials from a plurality of shipping destinations to a plurality of landing sites are collectively linked together. One purpose is to make it possible. It is another object of the present invention to include consideration of contract types of ships and to minimize transportation costs.

In addition, by taking into consideration items with close properties (items included in a prescribed range), the object of the present invention is to enable further suppression of inventory shortage and minimization of transportation costs as compared with each item individually.

(1) A system according to one embodiment of the present invention for achieving the above object includes a wiring plan for transporting a blended raw material of a plurality of items from a plurality of shipping destinations to a plurality of landing places, and the received blended raw materials, respectively. It is a compounding and wiring plan preparation system which prepares the compounding plan mixed in the said landing place, The 1st compounding plan preparation which produces a 1st compounding plan based on the acquisition target amount of the said compounding raw material preset for every said shipment place and every said item. It is a compounding and wiring plan preparation system provided with a part, the wiring plan preparation part which creates the said wiring plan based on the created said 1st formulation plan, and a database part which stores the created said wiring plan.

(2) In the compounding and wiring plan preparation system of the above (1), even when common constraints are used in the preparation of the compounding plan and the preparation of the wiring plan, the acceptance target amount and the stock situation of the compounding raw material are used. good.

(3) In the compounding and wiring plan preparation system of (1), the first compounding plan preparing unit includes the acceptance target amount of the compounding raw material, the stock situation of the compounding raw material, the properties of the compounding raw material, and the compounding raw material. A data introduction section for introducing data including a purchase cost and a transportation cost of the blended raw material, a formula model setting unit for setting a mathematical model representing supply and demand constraints of the blended raw materials and property constraints after mixing the blended raw materials, respectively; An optimization calculation unit which performs optimization calculation based on the objective function built in advance with respect to the purchase cost and the transportation cost by using the set formula model, and operates based on the result of the optimization calculation, To simulate the change in state and the change in properties after mixing of the blended raw materials. It may be provided with an output section for outputting a simulation result of the combination according to the plan with the simulator, the simulator.

(4) In the compounding and wiring plan preparation system of (3), the optimization calculating unit may perform optimization calculation further based on an objective function built in advance with respect to the relationship between the amount of the blended raw material and the argument target amount. .

(5) In the combination and wiring plan preparation system according to (3) or (4), the transportation cost introduced by the data introduction unit includes information of plates according to ships, ships, ships, and ships. The information of the plate for each port may be included.

(6) In the compounding and wiring plan preparation system of the above (1), the first compounding plan preparation unit further calculates an expected amount of use of the compounding raw material according to the created formulation plan, and the wiring plan preparation unit is the above. A list of ships listing a plurality of vessels operated on the basis of the expected use amount of the blended raw material, the target acquisition amount of the blended raw material, the stock situation of the blended raw material, the purchase cost of the blended raw material, and a plurality of charter party contracts; A data introduction unit which introduces data including the operational status and transportation cost of each of the vessels, and the vessel which selects the vessel as a candidate for wiring from the vessel list based on the operational status and prepares a vessel resource list To the resource list preparation unit, the operation constraints of the vessel included in the vessel resource list, the landing place A formula model setting unit for setting a formula model representing supply and demand balance constraints and acquisition target quantity constraints of the blended raw materials and the set formula model is used to calculate optimization calculations based on an objective function previously constructed with respect to the transportation cost. Optimization calculation unit to perform. A simulator comprising a stock trend simulator for simulating the trend of the stock situation, a ship operational status trend simulator for simulating the trend of the flight status, and operating based on the result of the optimization calculation, and a simulation result by the simulator You may be provided with the output part which outputs the said wiring plan.

(7) In the compounding and wiring plan preparation system of the above (1), the first compounding plan preparation unit further calculates an expected use amount of the compounding raw material according to the created formulation plan, and the wiring plan preparation unit is the above. The stock situation of the grouped blended raw materials, in which the blended raw materials of the plurality of the above items included in the prescribed ranges of the blended raw materials, the target target amounts of the blended raw materials, and properties are grouped and handled, the purchase cost of the blended raw materials, A ship list listing a plurality of vessels operated on the basis of a plurality of charter charter agreements, a data introduction unit for introducing data including the operational status and transportation cost of each of the vessels; and the vessel based on the operational status. Ship material which selects the ship which is a candidate of wiring object from list, and prepares ship finance list Supply list balance and supply and demand balance of the grouped blended raw materials, in which the blended raw materials of the plurality of the items included in the range of the ship list and the ship resource included in the ship resource list are defined and grouped and handled. A formula model setting section for setting a formula model representing a target quantity constraint, an optimization calculation section for performing optimization calculation based on an objective function built in advance with respect to the transport cost by using the set formula model, and a range in which properties are defined And a stock trend simulator for simulating the trend of the stock situation of the grouped blended raw materials, in which the blended raw materials of a plurality of the items contained in the grouped group are handled, and a ship operational status trend simulator for simulating the trend of the operational status; Operation based on the result of the optimization calculation Is, it may have an output for outputting a simulation result of the wiring plan of the simulator and the simulator.

(8) The compounding and wiring plan preparation system in any one of said (1), (3), (7) further has a 2nd compounding plan preparation part which prepares a 2nd compounding plan based on the created said wiring plan. The database unit may further store the second formulation plan.

(9) In the blending and wiring plan preparation system of (8), the second blending planning preparation unit is a stock schedule of the blended raw materials based on the created wiring plan, a stock situation of the blended raw materials, and the blended raw materials. The second data introduction section for introducing data including the cost, the purchase cost of the blended raw material and the transport cost of the blended raw material, and the supply balance constraint of the blended raw material and the properties after mixing of the blended raw materials, using the arrival schedule. A second optimization model setting unit for setting a mathematical model representing a constraint, and a second optimization calculation for performing optimization calculations based on an objective function built in advance with respect to the purchase cost and the transportation cost by using the set formula model. And a change in the supply and demand state of the blended raw material, operating based on the result of the optimization calculation. And a second simulator to simulate the trend of the aqueous phase after the mixing of the blended raw material, it may have a second output for outputting a simulation result of the combined plan by the simulator.

(10) In the formulation and wiring plan preparation system of (9), the same constraint conditions are set for the demand in the supply and demand balance constraints of the first formulation plan and the supply and demand balance constraints of the second formulation plan. In the supply and demand balance constraints of the first compounding plan, the supply target amount is set as a constraint with respect to the supply, and in the supply and demand balance constraints of the second compounding plan, the amount of stock of raw materials by the ship with respect to the supply. May be set as a constraint.

(11) In the compounding and wiring plan preparation system of the above (9), in the object function of the first compounding plan, the predicted plate for each item and each item is used, and in the object function of the second compounding plan, You may use plates by ship, by ship, or by ship.

(12) In the mixing | blending and wiring plan preparation system of said (1) or (3), in the said mixing | blending preparation plan created, the said compounding raw material of the said some raw material contained in the range in which a characteristic was prescribed | regulated may be grouped and handled.

(13) A method according to another aspect of the present invention for achieving the above object includes a wiring plan for transporting a blended raw material of a plurality of items from a plurality of shipping destinations to a plurality of landing places, and the received blended raw materials, respectively. A formulation and wiring plan preparation method for creating a formulation plan to be mixed at the landing site of the ship, and a first formulation plan preparation for creating a first formulation plan based on a target acquisition amount of the formulation raw material set in advance for each shipment place and each item. A process, a wiring plan preparation process of creating the said wiring plan based on the created said 1st compounding plan, and a database storage process of storing the created said wiring plan in a database are provided.

(14) A program according to another aspect of the present invention for achieving the above object is a program for operating a computer as each part of the combination and wiring plan preparation system of the above (1).

According to each aspect of the present invention, it is possible to create a batch plan by linking a blending plan for receiving and mixing a plurality of blended raw materials and a wiring plan for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites. In particular, in consideration of ships with different types of charter party contracts, an objective function constructed with respect to transportation costs can be prepared, and an optimization calculation can be performed based on this objective function. Thereby, it is necessary to minimize transportation costs, including whether to use the type of charter charter (continuous voyage, non-permanent ship, spot ship) and the structure of the end of the ship. Planning is possible. In addition, even in the compounding planning step, it is possible to prepare a plan in consideration of minimizing the transportation cost.

In addition, by considering items with close properties (items included in the defined range), optimization for further minimizing inventory shortages and minimizing transportation costs is possible compared with considering each item individually.

BRIEF DESCRIPTION OF THE DRAWINGS It is a figure which shows schematic structure of the compounding and wiring plan preparation system concerning each embodiment of this invention.
It is a figure which shows the example of the system structure containing a 1st or 2nd compounding plan preparation apparatus.
3 is a block diagram showing a basic configuration of a first or second compounding plan preparation device.
4 is a block diagram showing the configuration of a first or second compounding plan preparation device.
It is a flowchart for demonstrating the formulation planning preparation process by a 1st or 2nd formulation planning preparation apparatus.
It is a figure for demonstrating the outline | summary of formulation plan preparation.
7 is a diagram illustrating an example of a table for setting a plate to be used.
FIG. 8A is a diagram for explaining the constraint that the stock amount does not open more than a predetermined width from the acceptance target amount. FIG.
FIG. 8B is a diagram for explaining the constraint that the stock amount does not open more than a predetermined width from the acceptance target amount. FIG.
It is a figure for demonstrating the procedure of formulation planning preparation.
10 introduces the linear equation f '(x _A , x _B , x _C , ..., x _N ) instead of the nonlinear equation f (x _A , x _B , x _C ,..., X _N ). It is a flowchart which shows the process at the time of performing.
It is a figure which shows the example which created the compounding plan for every step.
It is a flowchart for demonstrating the wiring plan preparation process by a wiring plan preparation device.
FIG. 13 is a diagram for explaining a vessel list among introduction data. FIG.
14 is a view for explaining a ship operating situation among the introduction data.
FIG. 15 is a diagram for explaining a plate list of introduction data. FIG.
It is a figure for demonstrating the list of the ship cost of introduction data.
17 is a flowchart for explaining a vessel selection process.
FIG. 18 is a diagram showing a state in which a pattern of a combination of a shipping place and a landing place in a planning preparation period is created for the extracted continuous sailing ship.
It is a figure for demonstrating the raw material conveyance amount which needs to be supplemented with a spot line.
20 is a diagram for explaining a route list of spot lines.
21 is a diagram illustrating a relationship between time and stock amount.
22A is a diagram for explaining the constraint that the acceptance amount does not open more than a predetermined width from the acquisition target amount.
22B is a diagram for explaining the constraint that the acceptance amount does not open more than a predetermined width from the acquisition target amount.
Fig. 23 is a diagram schematically showing a relationship between macro optimization and micro optimization.
It is a figure for demonstrating the objective function aimed at leveling the load in a shipping place.
It is a figure for demonstrating the objective function aimed at leveling the load in a landing place.
26 is a diagram illustrating an example of a wiring plan.
It is a figure which shows the example of the hardware structure of the computer apparatus which can function as the mix | blending plan apparatus and wiring plan apparatus of this invention.

EMBODIMENT OF THE INVENTION Hereinafter, preferred embodiment of this invention is described with reference to an accompanying drawing. This embodiment demonstrates the example which mix | blended raw materials, such as an ore and coal, with the ship by the ship from the mine (shipment site) dotted with the whole steel mill, and mixes them. That is, in this example, the blended raw materials of the plurality of items are transported from the plurality of supply sources to the plurality of supply destinations by the ship and are received at the plurality of supply destinations. And this compounding raw material is mix | blended and used in each supply source. At this time, the blending plan of the blended raw materials of the plural items and the blended raw materials of the plural items are transported by the ship from the plural supply sources that are the shipping destinations to the plural supply destinations that are the landing sites. Formulation and wiring plan preparation suitable for preparing the wiring plan at the time of transportation by this ship are demonstrated below.

(System configuration)

BRIEF DESCRIPTION OF THE DRAWINGS It is a figure which shows schematic structure of the compounding and wiring plan preparation system which concerns on the 1st-4th embodiment of this invention. In addition, although the 2nd compounding plan preparation apparatus 300 is shown in FIG. 1, for example, this is not used in 1st Embodiment. Hereinafter, the outline | summary is demonstrated about the structure and process which are generally common to some embodiment. Then, the element and process contained in each embodiment are described in detail.

Reference numeral 100 denotes a first formulation planning preparation device, which prepares a formulation plan in which a plurality of items of raw materials are received and mixed based on the acceptance target amounts of the raw materials. Here, the formulation plan which mixes raw materials for every steel mill is created. Thereby, the planned use amount which shows how much raw materials are used every day in each steel mill is planned. This 1st formulation planning preparation device 100 functions as a 1st formulation planning preparation part in this invention.

Numeral 200 is a wiring plan preparation device, and based on the formulation plan created by the first formulation plan preparation device 100, a plurality of items of raw materials (such as ore and coal) are plural from a plurality of shipping sites (mines dotted around the world). A wiring plan to transport to the unloading site (steel mill). In this embodiment, it is aimed at making the wiring plan which minimizes the transportation cost by the total steelworks rather than leveling the transportation costs for every steel mill. Furthermore, it aims at making the wiring plan which minimizes the cost including the purchase cost of a raw material in addition to a transportation cost. This wiring plan preparation device 200 functions as a wiring plan preparation unit according to the present invention.

Reference numeral 300 denotes a second formulation planning preparation device, which creates a formulation plan that receives and mixes a plurality of raw materials based on the wiring plan created by the wiring plan preparation device 200. This 2nd formulation plan preparation device 300 functions as a 2nd formulation plan preparation part which is said by this invention.

Reference numeral 400 is a database, and stores data used by each device 100 to 300 in creating a plan, or a plan created by each device 100 to 300 in a manner that the computer 500 can refer to and modify. do. Thereby, collective management of the data which each device 100-300 uses in drawing up a plan, and the plan which each device 100-300 made, becomes possible, and the latest information can be shared.

Reference numeral 500 denotes a computer, which refers to or updates data stored in the database 400 or stores data in the database 400. Although only one computer 500 is shown here, in this embodiment, a plurality of computers are connected via a LAN or the Internet. The computer 500 includes, for example, a host computer called a process computer and the like, and a computer terminal that can access a database 400 installed in each of the mills (steel mill, head office, ship company, mine, etc.).

In addition, the system structure shown in FIG. 1 is only an example, It is not limited to this. For example, although each device 100-300 is shown to be comprised as one apparatus, each device 100-300 may be comprised by the computer system which consists of a some apparatus, respectively. In addition, when the 1st formulation planning preparation device 100 and the 2nd formulation planning preparation device 300 create a formulation plan with the same algorithm, for example, one computer system is the 1st formulation planning preparation device 100. And the second formulation planning preparation device 300. In addition, the case where the 1st compounding plan preparation part, the wiring plan preparation part, the database part, and the 2nd compounding plan preparation part mentioned in this invention is implement | achieved as one apparatus shall also be in the scope of the present invention.

(1st embodiment)

[1st formulation plan preparation device 100]

In the 1st formulation planning preparation device 100, based on the acquisition target quantity of a raw material, the formulation plan which receives and mixes several raw materials is created. The acquisition target amount is an acquisition target amount (a planned acquisition amount) for each mine (shipment site) and each item. Each mine has a contract with each item about how much to take over, for example, during the year. Dividing the acquisition amount in this period by the number of orders included in the corresponding period, the acquisition target amount of every order is obtained. In addition, in this specification, a pure refers to the unit of the period which divided | segmented month into three.

FIG. 2 is a diagram illustrating an example of the system configuration including the first formulation planning preparation device 100. As shown in FIG. 2, in preparing the formulation plan, the first formulation plan preparation device 100 accepts data setting by an operator or introduces data from the database 400. At this time, the data to be introduced includes, for example, the planning preparation period, the acquisition target amount, the stock situation of the raw materials, the properties of the raw materials, the purchase cost information indicating the unit price of the raw materials, and the transportation when using the vessel, which are necessary for formulating the formulation plan. Constraints and prerequisites including cost information are included. The data on the properties of the raw materials includes physical and chemical properties, such as the degree of coalification and the content of each component.

The first blending plan preparation device 100 executes a simulation to create a blending plan in which a variety of raw materials are received and mixed. The first blending plan preparation device 100 calculates the amount of usage (mixing ratio) and the amount of each item as the blending plan so as to satisfy supply and demand balance constraints of raw materials and property constraints after mixing. Although details will be described later, the first blending plan preparation device 100 applies the supply and demand balance constraints of the raw materials, which are constructed in accordance with repair planning methods such as LP (linear planning method), MIP (mixed water purification planning method), and QP (secondary planning method). The formulation plan is optimized by setting a mathematical model (also referred to as a "supply and balance model") and a mathematical model (also referred to as a "model model") indicating the property constraints after mixing.

Setting of a mathematical model is a series of processes also called expansion of a mathematical model, and is performed by each part or method of the apparatus of this embodiment including the process demonstrated below. In the present embodiment, the mathematical model is constructed and formulated in an abstract form in advance so as to respond to changes in respective conditions such as the number of ships and the number of ports. About this mathematical model, the maximum number of subscripts of each array (for example, the number of ships), the coefficient of a formula, the value of a constant, etc. are specifically determined according to the conditions of plan drawing.

The display unit 303 displays the amount of use (compound ratio), the amount of stock received, the stock trend graph, and various documents of each item determined by the first formulation planning preparation device 100.

The supplier evaluation unit 304 evaluates the obtained compounding plan from various points of view (for example, inventory trends, properties, etc.), and corrects the compounding ratio or the like as necessary if the result is not satisfactory. In that case, the weight of an objective function and the index of evaluation are changed as needed, and the target period and plan confirmation period which set a mathematical model are changed. In addition, it is possible to set a mathematical model that reflects the intention of the operator, such as fixing the amount of use of all or only designated processing. And the 1st compounding plan preparation apparatus 100 recreates a compounding plan again.

3 is a block diagram showing a basic configuration of a first compounding plan preparation device. As shown in FIG. 3, the first blending plan preparation device 100 includes a simulator (including a stock development simulator 311 and a constellation simulator 312) and a model functioning as a mathematical model setting unit according to the present invention. It includes a setting unit (including supply and demand balance model setting unit 313 and constellation model setting unit 314), and a planning unit 315 functioning as an optimization calculation unit according to the present invention, and also has an input / output unit. .

The stock trend simulator 311 is a simulator for calculating the supply / demand state (stock trend) of each raw material. The property simulator 312 is a simulator for calculating the property after mixing raw materials. The inventory trend simulator 311 and the property simulator 312 interlock with each other, and calculate the stock trend of raw materials and the property after mixing.

In the present embodiment, for example, the planning preparation period, the acquisition target amount, the stock situation of the raw materials, and the properties of the raw materials, which are required in formulating a formulation plan, which performs a setting process of the formula model based on the input data 316, for example. Purchase cost information indicating the unit price of the raw materials, transport cost information when using the ship, and the like. Based on the pre-set time precision for the optimization period set in advance from the drafting start date of a blending plan, the hydraulic constant planning methods, such as LP (linear programming method), MIP (mixed-integer constant planning method), and QP (secondary planning method), etc. In accordance with the above, the mathematical expression model indicating the supply and demand balance constraints (stock constraints) is set by the supply and demand balance model setting unit 313, and the mathematical expression model indicating the property constraints is set by the property model setting unit 314.

By using the formula model set by the supply / demand balance model setting unit 313 and the property model setting unit 314, it is possible not to drop the inventory, satisfying the required properties, and furthermore, the cost (purchasing cost and transportation cost of raw materials). The planning unit 315 performs an optimization calculation so as to create a formulation plan by minimizing this. Based on the results of this optimization calculation, calculation instructions for the inventory trend simulator 311 and the property simulator 312 are created. In response to this calculation instruction, the stock trend simulator 311 simulates the stock trend, and the property simulator 312 simulates the properties of the products and semi-finished products manufactured according to the plan. For example, in the steel industry, properties such as coke (product) obtained by mixing and solidifying coal and solidifying slab (semi-finished product) of solidified molten steel obtained by reducing iron ore are simulated.

According to the first formulation planning preparation device 100, the calculation instruction based on the result of the optimization calculation performed by the planning unit 315 is not performed based on a predetermined rule as in the related art, but it is a stock transition simulator. 311, and outputs to the constellation simulator 312. For this reason, it becomes possible to reliably perform the optimal calculation instruction according to the idea at that time.

For example, as shown in FIG. 7, the simulation by the stock trend simulator 311 and the property simulator 312 is performed about preset plan confirmation period. Upon completion of this simulation, the drafting start date is updated, and the supply-demand balance model setting unit 313 for the new optimization period is based on the final state of the plan-determination period before the update, that is, the inventory trend at the drafting start date after the update and the property information. ), A mathematical model representing the stock constraints is set, and the mathematical model is set by the constellation model setting unit 314. The formula model after setting is provided to the planning unit 315. In this way, when the mathematical expression model set based on the inventory trend and the constellation information is provided to the planning unit 315, optimization calculation is performed using this.

As described above, each simulator (stock trend simulator 311, constellation simulator 312), each model setting unit (supply balance model setting unit 313, constellation model setting unit 314), and planning unit 315 ), The optimal blending plan can be created. That is, the simulation performed in this embodiment is performed based on the result of optimization calculation, not the simulation based on the predetermined | prescribed rule like the conventional one. This makes it possible to reliably obtain the theoretical optimal solution only by executing one simulation. With this configuration, it is not necessary to evaluate the simulation results and execute the simulation several times or repeatedly as in the prior art, so that the simulation results 317 can be produced quickly and with high accuracy. Therefore, even if the target for creating the formulation plan is large, it is possible to create within practical time.

In addition, in the conventional method, when the planning preparation period becomes long, the period to be calculated becomes long, and accordingly, the problem scale becomes large rapidly, and thus there is a problem that the solution is impossible. In this method, however, the problem size can be reduced by dividing the entire planning period into shorter optimization periods. This makes it possible to solve problems even if the overall planning period is long. The simulation result 317 obtained as mentioned above is output as a compounding plan.

In addition, even when the scale of the model set by the supply / demand balance model setting unit 313 and the constellation model setting unit 314 is very large or when the constraints are very large and complicated, the inventory trend simulator 311 and the constellation simulator ( Among the supply and demand balance constraints and property constraints described in 312), only the important portions having a large influence on the formulation plan preparation are extracted, and only the extracted portions are introduced into the supply and demand balance model setting unit 313 and the property model setting unit 314. good. Thereby, optimization calculation can be performed within a practical time by making the magnitude | size of the mathematical model of the supply-demand balance model setting part 313 and the constellation model setting part 314 into an appropriate range. Since the inventory trend simulator 311 and the property simulator 312 can describe both supply-demand balance constraints and property constraints to be considered, it is assured that the blending plan created by executing one simulation is practically executable.

As described above, in the present embodiment, the simulator (stock trend simulator 311, constellation simulator 312) and the model setting unit (supply balance model setting unit 313, constellation model setting unit 314) and the plan Unit 315 is linked to create a formulation plan. For this reason, the following effects are acquired. (1) A formulation plan can be created without repeating the simulation. (2) Calculation time can be shortened by introducing only the restriction of the important part which has a big influence on formulation planning to the planning part 315. FIG. (3) It is possible to solve large-scale problems.

Hereinafter, each step of the structure of the 1st formulation planning preparation apparatus 100 and the formulation planning preparation method performed using this apparatus is demonstrated in detail. FIG. 4: is a figure which shows the detailed structure of the formulation planning preparation apparatus with respect to the basic structure of the 1st formulation planning preparation apparatus 100 demonstrated using FIG. 5 is a flowchart which shows each step of the compounding plan preparation method performed using this apparatus.

As an outline of formulation planning, for example, as shown in FIG. 6, balancing supply and demand of raw materials (items) in a plurality of steelworks (both ports) a to c, (do not drop inventory of each item A to N). Etc.) to satisfy the required properties, to minimize the cost (purchasing cost and transportation cost of raw materials), and to use the above mentioned conditions as a blending plan for each item A to N of steel mills a to c. Calculation and adjustment processes such as determining the compounding ratio, loading amount, and the like. Here, the predetermined usage amount which is the total amount of the usage amount per steel mill is given as input data. For this reason, it becomes a compounding ratio (%) = consumption / anticipated usage amount x100. For this reason, when one of usage-amount and a compounding ratio is determined, the other will be determined.

(1) Introduction of input data (input data introduction unit 351 of FIG. 4, step S301 of FIG. 5)

The information necessary for this processing (acquisition target quantity, stock situation of raw materials, properties of raw materials, purchase cost information indicating the unit price of raw materials, transportation cost information when using a ship), etc. is read online, and an operator corrects as necessary. Add.

Here, the acquisition target amount introduced by the input data introduction unit 351 is information indicating the acquisition target amount (acquisition scheduled amount) for each mine (shipment site) and for each item. Each mine has a contract for how much of the raw material to take over (item amount) for each item of the raw material, for example, in a period such as a year. Dividing the total acquisition amount by the number of months over this period yields the monthly acquisition target amount. It is required to arrive near this acquisition target amount. However, the deviation of the takeover amount of tens of thousands of tons per year is within the allowable range by negotiation with the mine. In addition, depending on the contract, a contract such as not accepting a predetermined period of time for a predetermined item may be considered. Such exceptional conditions may be included in the calculation. For example, suppose that the raw material A is 50,000 tons in one month, and the deviation from the target is 60,000 tons per year (5,000 tons per month). In this case, about the arrival plan of the month, the range between an upper limit (arrival plan quantity upper limit) 50,000 tons + 5,000 tons, and a lower limit (arrival plan quantity lower limit) 50,000 tons-5,000 tons becomes an allowable range.

The stock situation of raw materials is information which shows the stock amount (ton tonnage) according to steel mills and items in the first day of a plan making period.

The properties of the raw materials are information indicating the properties of components and the like for each raw material. For example, properties of iron ore that is a raw material include property information of raw materials such as Fe ₂ O ₃ , Fe ₃ O ₄ , SiO ₂ , and Al ₂ O ₃ .

The purchase cost information of the raw materials is information indicating the unit price [$ / ton (t, t)] of the raw materials for each mine (site) and for each item.

As shown in Figs. 15 and 16, the transportation cost information when using a ship is determined by the red port according to the case of using a plate listed in the ship list and the ship listed in the ship list. Information representing a ship fee. In addition, the transportation cost information at the time of using a ship also includes the information which shows the estimated plate by each item and the port (an unloading place). The transportation cost is uniquely determined by the plate-by-ship, ship-by-boat, and ship-by-port plates described above. However, in the work stage of the 1st compounding plan preparation apparatus 100, the ship which loads a raw material is not determined about arrival. For the raw materials whose ships to be loaded are undetermined, plates for each item and each port are needed to estimate the transportation cost of the raw materials. Here, the plate for each item and for each port is originally different in the plate depending on the choice of a vessel on which the raw materials are to be loaded, and thus cannot be determined uniquely. Therefore, instead of the item-specific and port-specific plates, information about the estimated predicted plates is obtained by item and port. As the predicted plate for each item and port, for example, a plate of the past result for each item and port, which is set based on experience, etc. Predicted plates by item and port are considered in advance.

The input data introduction part 351 and step S301 demonstrated above are examples of the data introduction part of the 1st compounding plan preparation part which it says in this invention, and the process by it.

(2) Setting of compounding plan preparation period (plan preparation period setting part 352 of FIG. 4, step S302 of FIG. 5)

Set a period of time to develop a formulation plan. This preparation period allows setting any period according to the needs of the planner. Here, for example, 10 days are drawn up.

(3) Setting of the compounding plan preparation time precision (time precision setting unit 353 of FIG. 4, step S303 of FIG. 5)

Set the time precision and simulation precision for creating a formulation plan. This time precision and simulation precision allow arbitrary accuracy to be set individually according to the needs of the planner. For example, in the first half of the planning period, which requires detailed precision of the draft, the precision is strict, and the roughness is not so strict in the second half of the planning period. Efficient planning is possible.

(4) Setting of the optimization period (optimization period setting unit 354 in FIG. 4, step S304 in FIG. 5)

Set an optimization period to create a formulation plan. This optimization period makes it possible to set any target period individually according to the needs of the planner. Here, as an example, the optimization period is three days through the plan preparation period.

(5) Setting of plan confirmation period (plan confirmation period setting part 355 of FIG. 4, step S305 of FIG. 5)

Set a plan confirmation period to finalize the formulation plan. This plan determination period enables the arbitrary period to be set individually according to the needs of the planner. For example, the planning confirmation period is shortened in the first half of the planning period that requires detailed precision in the drafting, and the planning confirmation period is extended in the second half of the planning period that is sufficient by only rough planning. This enables efficient plan creation with a short calculation time while having sufficient precision. Here, as an example, the plan determination period is set to one day. In this case, about the compounding plan obtained as a result of the simulation based on the solution to a mathematical formula model, the 1st day is decided through a plan preparation period.

(6) Set supply and demand balance constraints of the formulation plan as a mathematical model (supply and balance model setting unit 313 of the basic configuration diagram of FIG. 3, supply and demand balance model setting unit 356 of FIG. 4, step S306 of FIG. 5)

Based on all or part of the data introduced by the input data introduction unit 351, the set supply and demand balance is set for the mathematical expression model with the set time precision.

The variable which shows the usage amount of each item is defined as shown to following (formula 1). In addition, the variable which shows the stock amount of an item is defined as shown to following (formula 2). In addition, the variable which shows the stock amount of each item is defined as shown to following (formula 3). In addition, "small" in a formula represents the steel mill corresponding to a landing place in this embodiment.

A mathematical model set on the basis of supply and demand information, that is, a supply and demand balance constraint model, is shown below. Here, it is required that the inventory amount of each item is equal to or greater than a value called a constant safety inventory amount. Constraints in this case are represented by the following formula (4).

In addition, the stock amount of each item is determined from the stock amount of the previous day, the stock amount of the previous day, and the usage amount of the previous day. The constraint expression showing the relationship in this case is represented by the following (formula 5). That is, the stock amount of the day becomes the value which subtracted the consumption amount of the day from the value which added the stock quantity of the previous day and the quantity received (unloaded) on the day.

In addition, the total of the days with the usage amount of each item needs to correspond with the usage planned to the total of all the items of the day. The constraint expression showing the relationship in this case is represented by the following (formula 6).

In addition, in view of factors such as the purchase of various raw materials, an operator sets a target blending ratio and requires that a blending plan for realizing a blending ratio close to the target blending ratio given thereto is created. In other words, when the blending ratio is far from the assumption of the operator, it is assumed that the estimated purchase amount cannot be satisfied, the purchase amount is exceeded, or the operation equipment is subjected to unreasonable operation. For this reason, it is necessary to output the compounding ratio near the compounding ratio provided as a target. Constraints for realizing the above functions are shown below. That is, the value which subtracted the use target amount (targeting compounding ratio) (constant) from the usage amount of an item is defined as a variable of the excess amount from a use target amount. Here, since the closer the usage amount and the usage target amount are, the better the plan is, the smaller the excess amount is. For this reason, as described below, this excess is added as an item of the objective function and minimized by optimization. Similarly, the value obtained by subtracting the use amount from the use amount of the item is defined as a variable of the shortage from the use amount. Here, the usage amount and the usage target amount are better plans that take a closer amount, so the smaller the shortage, the better. For this reason, as described below, this lack is added as an item of the objective function and minimized by optimization. In this case, the constraints representing the relationship between the amount used, the target amount used, the excess amount and the insufficient amount of each item are represented by the following equation (7). In other words, when an excess occurs, the excess amount is subtracted from the amount used, and when a shortage occurs, the amount is insufficient to coincide with the use target amount.

Moreover, when the compounding ratio of the previous day and the compounding ratio of the next day largely differ, it will cause difficulty in operation. That is, it increases the preparation time for using other raw materials or causes a malfunction of the equipment. For this reason, the compounding plan which does not differ greatly between the compounding ratio of the previous day and the compounding ratio of the next day is calculated | required. In order to realize the said function, the variable which shows an upper limit with respect to the difference of the usage-amount of the said item of the day and the usage-amount of the previous day is defined as shown in following formula (8).

Constraints for realizing the above using this variable are shown in Equation 9 below. That is, the value which subtracted the use of the day before the day from the usage-amount of the said item of the item shall be less than or equal to the difference between the usage-amount of the said day, and the use of the day before. In this case, the more suitable the usage amount of the day and the usage amount of the day before the day are taken, the more suitable the plan is. For this reason, as described below, this excess is added as an item of the objective function and minimized by optimization. Similarly, the value obtained by subtracting the consumption amount of the item from the usage amount of the previous day of the item is also formulated as a pharmaceutical formula.

In addition, the quantity of each item to be received is required to be in the range of the quantity provided as a quantity scheduled to be received. Constraints representing the relationship in this case are represented by the following formulas (10) and (11). In other words, the total amount of the stock received in the month needs to be equal to or less than the upper limit of the estimated stock of the month and more than the lower limit of the planned stock.

In addition, in the 1st compounding plan preparation apparatus 100, a compounding plan is created based on an acquisition target amount. As will be described later, a series of processes including optimization (steps S103 to S106) and simulation (S107) can be executed repeatedly in a plurality of loops. In the first loop, the mathematical model described later is set based on the data introduced in step S301, and after the next loop, the mathematical model is set to reflect the simulation result in the simulator. In the formula model setting regarding the acceptance target amount constraint, for example, the acceptance amount (loading amount) to be optimized does not open more than a certain width from the acquisition target amount, and the acceptance of the acquisition (as described above, the predetermined period for Considerations may not be undertaken). Here, as a method of formulating the constraint that the takeover amount does not open more than a predetermined width from the takeover target amount, as shown in FIG. 8A, for example, simply set the upper and lower allowable ranges for the takeover target amount of each order (or monthly), A method or configuration can be considered which makes the constraint that the loading amount falls within the allowable range. In that case, however, if, for example, the amount of stock satisfies the lower limit of the allowable range, but the situation continues to fall below the orderly acquisition target amount, the annual cumulative amount of stock may be lower than the annual acquisition target amount. Therefore, as shown in Fig. 8B, the accumulation of the acquisition target amount and the accumulation of the acquisition amount from the beginning of each draft (or monthly) to the corresponding order are calculated, and the difference between the accumulation of the acquisition target amount and the accumulation of the acquisition amount is made small (or at least, It is appropriate to set a constraint such that the upper and lower limits are not exceeded. In order to formulate the above constraint, variables of excess amount and deficit from the accumulation of the acquisition target amount of each order are defined.

In addition, it defines the variable of accumulation of the acquisition amount of each order.

First, the constraint expression representing the accumulation of the acquisition amount of each item is represented by the following expression (12). In other words, the cumulative amount of acquisitions is the sum of the amounts received in the period from the drafting start date to the order in question.

Constraints representing the relationship between the cumulative target amount of each item, the excess amount, and the shortage amount are represented by the following equation (13). In other words, subtracting the excess or subtracting the excess from the accumulating amount coincides with the accumulating target. Here, the cumulative acquisition amount and the acquisition target accumulation amount are more suitable plans, so the excess and deficit amount is better. For this reason, as will be described later, this excess and deficit are added as items of the objective function and are minimized by optimization.

In addition, the supply-demand balance constraint mentioned above is an example, You may change into another constraint or add another constraint.

(7) Setting the Constraint Constraint of the Mixture Plan to the Equation Model [Constellation Model Setting Unit 357 including the Contour Model Setting Unit 314 of the Basic Configuration Diagram of FIG. 3, Linearization Unit 357a of FIG. 4, and FIG. 5. Steps S307, S307a]

Based on all or a part of the data introduced by the input data introduction unit 351, the constraints are set to the mathematical model using the set optimization period and time precision. Examples of the properties of the raw materials used in preparing the iron ore blending plan include iron powder, SiO ₂ , Al ₂ O ₃ , SiO ₂ , and the like. As a property at the time of preparing the mixing | blending plan of coal, CSR (strength after a hot reaction), DI (coke strength), VM (volatile content), expansion pressure, etc. are mentioned, for example. These properties need to satisfy the required property constraints. An example of the property model after mixing was shown by (formula 14). In addition, although the example which has a lower limit S is shown in (Formula 14), there may be a case where it has an upper limit, or may have both an upper limit and a lower limit.

x _A to x _N : Mixing ratio of raw materials (item) A to N

S: Lower limit (constant)

Here, for many constellations, the formula f (x _A , x _B , x _C ,..., X _N ) included in the constellation model is linear with respect to the blending ratio, as shown in the following formula (Formula 15). do.

W _A to W _N : Properties of the ingredient included in item i for each item

For example, the mixing conditions, the mixing ratio of the item A 40%, the SiO ₂ component of the item A 1%, a 60% composition ratio of the item B, the SiO ₂ component of the item B 2% with respect to SiO ₂ In this case, the properties of the SiO ₂ component after mixing are 1 × 0.4 + 2 × 0.6 = 1.6%.

By the way, depending on the property, the expression f (x _A , x _B , x _C , ..., x _N ) representing the property may be nonlinear. In this case, as described below, in the linearization unit 357a, the linear equation f '(x _A , x instead of the nonlinear equation f (x _A , x _B , x _C ,..., X _N ) is used. _B , x _C ,..., X _N ) are introduced to form a mathematical model.

The processing in the linearization unit 357a will be described. If the formula f (x _A , x _B , x _C ,... X _N ) representing a constellation is nonlinear, the linear formula f '(x _A , x _B , x _C ,... x _N ) is introduced. Formula of linear f '(x _A, x _B, x _C, and and and, x _N), the formula for the non-linearity f forming the lower limit of (x _A, x _B, x _C, and and and, x _N) It is conceivable to establish a relationship of (e.g., Eq. 16). In addition, (Equation 16) does not always need to be established, but just needs to be established in the required range.

For example, as a linear expression f '(x _A , x _B , x _C , ..., x _N ), a weighted average represented by (Equation 17) is considered. The weighted average is a value obtained by calculating the properties when 100% of a single item is used from the nonlinear formula f (x _A , x _B , x _C , ..., x _N ), multiplying the compounding ratio, and adding the used items. .

In order to simplify the explanation, an example in which the blending ratio of Item A is 90% and the blending ratio of Item C is 10% is considered. In this case, the weighted average of the linear expression f '(90, 0, 10, ..., 0) is represented by the following formula.

f '(90, 0, 10, ..., 0)

= 0.9 x f (100, 0, ..., 0) + 0.1 x f (0, 0, 100, ..., 0)

If the weighted average satisfies (Equation 16) from past performances or the like, this weighted average can be used as a linear equation f '(x _A , x _B , x _C , ..., x _N ). . In other words, if the weighted average? Is taken as a constraint, the possibility of being formulated is obtained by considering that (Equation 14) will hold.

In the linearization unit 357a, as shown in (Equation 14) ', the nonlinear equation f (x is a lower limit for the linear equation f' (x _A , x _B , x _C , ..., x _N ). _A mathematical model is set by setting a temporary lower limit S '= S-s (s: offset value) smaller than the lower limit S for _A , x _B , x _C , ..., x _N ).

As mentioned above, the case where the property constraint after mixing has a lower limit was demonstrated to the example. In addition, the above-mentioned property constraints are an example, and you may change into another constraint (including the case where the property constraint after mixing has an upper limit), and may add another constraint.

Supply-demand balance model setting unit 356 (provided supply-demand balance model setting unit 313 in FIG. 3) and step S306 and constellation model setting unit 357 (constellation model setting unit 314 in FIG. 3) and step S307 described above. S307a is a modification model setting part and the processing example by that of the 1st compounding plan creation part which are said by this invention.

(8) Immobilized Extraction Processing (Fixed Extraction Processing Unit 358 of FIG. 4, Step S308 of FIG. 5)

As shown in FIG. 9, the fixed, that is, unchangeable among the ship's port, shipment item, shipment amount, boat port, landing item, and landing amount which are the items of a wiring plan are extracted. According to the conditions given in advance, when "shipping port" and "shipment goods" are immobilized with respect to each charter ship, the plate according to a ship, a ship port, and a ship port (refer FIG. 15) is used. That is, since the molten iron for loading raw materials is determined, the use of plates for different ships, ships, and ships makes it possible to accurately calculate transportation costs at the time when the steel mill to receive the raw materials is determined by optimization.

When none of the items is immobilized, or when only the "red port" is immobilized, the predicted plates for each item and both ports are used. That is, when the port and the shipment item are not determined, the port and the shipment item which are related to the vessel can be changed so that the port and the shipment item which are cheaper than the said port and the shipment item are used using the optimization mentioned later. It is possible to examine the presence or absence. In this case, by using the predicted plate by item and by port, it is possible to optimize the plan to change the ship's port and loading item to the ship and shipping item having lower transportation cost than the port and loading item. Evaluate and review. This makes it possible to prepare a plan having a lower transportation cost. Regarding the same molten iron, the state of the record in which immobilization is not impersonated is considered to be the immobilization state of the molten iron. This immobilization extraction process does not need to be the timing shown in FIG. 5, and may be performed, for example, when starting a formulation plan preparation.

In this embodiment, since the wiring plan does not exist, that is, the wiring plan after the drafting start date has not been established at all, and the formulation and wiring plan are prepared from the beginning, the vessel to be subjected to the immobilization is an example. There is no information. However, the present invention can also be applied to the modified embodiment. For example, after devising three months' combination / wiring plan from the date of drafting and planning for one month, two months are referred to the last draft, and one month is completely new. A blending / wiring plan may be formulated while rolling, such as drafting a blending / wiring plan. In such an operation, when establishing a compounding plan, a wiring plan exists for a part of the date close to the drafting start date of the plan creation period, and a part of the chartered ship is fixed, and the remaining period for the above in the plan creation period. For, there is no wiring plan at all. In this modified embodiment, when carrying out the compounding plan, there is a ship to be immobilized. In such an embodiment, by using the immobilization extraction process, it is possible to gradually improve the wiring and the compounding plan while respecting the existing conditions.

(9) Optimize the formulation planning formula model based on the objective function (the planning unit 315 of FIG. 3, the formulation planning evaluation unit 359 of FIG. 4, and step S309 of FIG. 5).

The supply-demand balance model and the constellation model made up of the linear and integer constraints set as described above are combined formulation formula models, and LP (linear programming), MIP (mixed-integer programming) and QP ( By calculating the problem as an optimization problem by a hydraulic programming method such as the second planning method), the optimum amount of use and the amount of stock are calculated.

Here, the example in the case of using a linear formula with respect to the objective function is shown. In this embodiment, it aims at minimizing cost (purchasing cost of a raw material, and transportation cost), and an example of the objective function J is shown to (Equation 17). In obtaining using the objective function, the purchase cost information and the transportation cost information set in step S308 are used.

Here, in this embodiment, when the wiring plan does not exist in the first compounding plan, that is, the wiring plan after the drafting start date is not established at all, and the compounding and wiring plan are prepared from the beginning, There is no ship information to be immobilized. For this reason, in (Equation 17), the term regarding the plate according to a ship, a ship port, and a ship port (right side 2) does not exist.

In addition, the 1st compounding plan preparation apparatus 100 aims at the relationship between the amount of raw material received and the acquisition target amount, ie, the amount of incoming raw material to be optimized not exceeding a certain width or more from the acquisition target amount.

For example, construct an objective function aimed at minimizing the difference between the net stock and the net goal target. Alternatively, an objective function is constructed for the purpose of minimizing the difference between the accumulation of the acquisition amount (accumulation of the shipment amount) and the accumulation of the acquisition target amount. Specifically, the stock amount of each item is counted in net units (or monthly units), and the accumulation until then is considered (stock accumulation). Moreover, the acquisition target amount of each item is aggregated in net unit (or monthly unit), and the accumulation until then is set as a target value (acquisition target amount accumulation). And the objective function is constructed to aim to minimize the difference between the accumulation of incoming stock and the accumulation of acquisition target quantity. That is, the objective is to reduce the difference between the accumulation of the acquisition target amount and the accumulation of the acquisition amount in consideration of the accumulation of the acquisition target amount and the acquisition amount. In the present embodiment, in consideration of accumulation, an item for minimizing the total amount of excess and deficit from the acquisition target accumulation amount of every order is added to the objective function.

(Equation 17) and (Equation 18) are examples of the objective function, and may be replaced with other objective functions or other objective functions may be added.

For example, when it is necessary to bring the compounding plan closer to the compounding ratio closer to the target compounding ratio given, and it is necessary to prepare a compounding plan in which the compounding ratio of the previous day and the compounding ratio of the next day do not significantly differ. Adds to the objective function an item that minimizes the difference between the excess amount, the shortage amount, and the usage amount on the day and the usage amount on the day before.

By subtracting the above-described formula (formula model) by the mixed constant programming, an optimal solution to the formulation plan formula model in which the supply-demand balance model and the property model are combined is obtained.

The blending plan evaluating part 359 (plan part 315) and step S309 demonstrated above are examples of the optimization calculation part of the 1st blending plan preparation part which this invention says, and the process by it.

(10) Determination of the calculation result by the optimization calculation (the calculation result determination part 360 of FIG. 4, step S310, S311 of FIG. 5)

It is determined whether or not the result obtained by the optimization calculation using (Equation 14) satisfies the mathematical model f (x _A , x _B , x _C , ..., x _N ) ≥S containing a nonlinear formula. do. As a result, if the mathematical model f (x _A , x _B , x _C ,..., X _N ) ≥S including the nonlinear equation is satisfied, the calculated result is calculated for the constellation simulator 362 described later. Run the simulation as directed. If the result does not satisfy the mathematical model f (x _A , x _B , x _C ,..., X _N ) ≥S containing a nonlinear formula, then the mathematical model f '(x _A containing a linear formula , x _B , x _C ,..., x _N ) ≥S 'is adjusted (step S311 in FIG. 5). Specifically, the temporary lower limit S 'is slightly increased.

10 is step S307 to S310 processing, that is the formula of the non-linearity f (x _A, x _B, x _C, and and and, x _N) linear equation in place of f '(x _A, x _B, x _C, and It is a flowchart which shows the process at the time of introducing _xN ). In step S401, instead of the supply-demand balance model and the constellation model [non-linear equations f (x _A , x _B , x _C ,..., X _N ), linear equations f '(x _A , x _B , x _C , Constructed by introducing x _N ), and performing an optimization calculation based on the objective function J.

In this case, as shown in (Equation 14) ', as a lower limit for the linear expression f' (x _A , x _B , x _C , ..., x _N ), the nonlinear equation f (x _A , x _The temporary lower limit S '= S-s (s: offset value) smaller than the lower limit S for _B , x _C ,..., X _N is set.

Next, in step S402, the result obtained by optimization calculation using a mathematical model f '(x _A , x _B , x _C ,..., X _N ) ≥S' containing a linear formula is a nonlinear formula. It is determined whether or not the mathematical model f (x _A , x _B , x _C ,..., X _N )? That is, the calculated result (the usage amount (mixing ratio) of each item A to N) by the optimization calculation in step S401 is substituted into (Equation 14), and it is determined whether or not (Equation 14) is established.

As a result of Step S402, (Formula 14) is established, the process ends (step S412 of Fig. 10). On the other hand, if (Formula 14) does not hold, the routine proceeds to step S403, where the temporary lower limit value S 'is slightly increased by a predetermined increase / decrease width, and the process of step S401 is executed again. That is, convergence calculation which repeats the calculation by optimization calculation is performed by increasing the temporary lower limit S 'by a small amount until (Equation 14) is established.

In addition, in this embodiment, although the case where the property constraint after mixing has a lower limit was demonstrated as an example, the same also applies to the case where it has an upper limit. In this case, the linear equation f '(x _A , x _B , x _C , ..., x _N ) is the upper limit of the nonlinear equation f (x _A , x _B , x _C , ..., x _N ). I think to achieve. Further, in step S401, as the upper limit value for the linear expression f '(x _A , x _B , x _C , ..., x _N ), the nonlinear expression f (x _A , x _B , x _C , ... , x _N ) is set to a temporary upper limit value that is larger than the upper limit value.

(11) Simulate the stock trend based on the solution obtained (the stock trend simulator 311 of FIG. 3, the stock trend simulator 361 of FIG. 4, and step S312 of FIG. 5).

Based on the solution to the formulation planning formula model and all or a part of the data introduced by the input data introduction unit 351, the set plan is set for all or part of the set plan determined periods. Run the simulation with creation accuracy. In this simulation, simulations including constraints that cannot be included in the formulation planning formula model, for example, conditions that are not based on a constant rule, such as difficult to formulate, and rules of operation are simulated. This changes the solution resulting from the solution to the formulation planning formula model into a formulation plan that can be used without problems in actual operation. This makes it possible to formulate a formulation plan that takes into account the time accuracy required in actual operation and detailed constraints required for actual operation.

In addition, as an example of constraints that are difficult to handle in the mathematical model, the preparation time of preparation of equipment when the compounding ratio is changed is accurately introduced by simulating and formulating a compounding plan considering the detailed constraints required for actual operation. This becomes possible.

(12) Simulate the constellation based on the obtained solution (the constellation simulator 312 of FIG. 3, the constellation simulator 362 of FIG. 4, and step S313 of FIG. 5)

The solution to the formulation planning formula model is based on all or a portion of the inventory, simulated by the inventory trend simulator 361, and all or a portion of the data introduced by the input data introduction unit 351. With respect to the set planning decision period, simulation of the properties is performed with the set planning accuracy. As a result of the simulation, results of properties after mixing of the raw materials are obtained. In this simulation, simulations including constraints, operation rules, and the like, which were not included in the formulation planning formula model are performed, thereby changing the solution resulting from the formulation planning formulation model into a formulation plan that can be used without problems in actual operation. This makes it possible to formulate a formulation plan that takes into account the time accuracy required in actual operation and detailed constraints required for actual operation.

The stock change simulator 361 (the stock change simulator 311) and the step S312 and the constellation simulator 362 (the constellation simulator 312) and step S313 which were demonstrated above are the simulators of the 1st compounding plan preparation part which this invention says, and Is an example of processing.

(13) Confirmation of formulation plan (determination part 363 of FIG. 4, step S314 of FIG. 5)

The plan confirmation period set from the compounding plan derived by the said inventory trend simulation and the property simulation is confirmed. As shown in FIG. 7, since the plan determination period is set to 1 day in this embodiment, the first 1-day portion of the created formulation plan is determined. About the part which did not enter the said plan confirmation period among the created combination plans, the plan is discarded without confirmation.

(14) It is determined whether the plan for the period for planning creation or the period for the plan determination period is confirmed (the judgment unit 364 of FIG. 4, step S315 of FIG. 5).

It is judged whether the plan confirmation period determined by the execution time of this step includes the whole plan preparation period set previously. In the present embodiment, since the plan creation period is 10 days, the plan for the plan confirmation period is determined at the time when the plan is confirmed in the tenth loop. For this reason, the formulation plan for 10 days is created and a process is complete | finished at the time of finalizing a plan in a 10th loop.

(15) Update of drafting start date (update part 365 of FIG. 4, step S316 of FIG. 5)

When the planning decision period determined at the time of executing this step does not include the entire planning preparation period set in advance, the date and time immediately after the formulation planning period determined in the above formulation plan is set as a new drafting start date. In this embodiment, as shown in FIG. 7, in the first loop, the drafting start date, which was originally 0 o'clock on the first day, is updated to 0 o'clock in the second day, and in the second loop, the drafting start date, which was initially 0 o'clock in the second loop, is updated to 0 o'clock on the 3rd day.

(16) Output of compounding plan [output part 366 of FIG. 4, step S317 of FIG. 5]

The compounding plan created as described above is displayed on the display unit 303 by the output unit 366 or data is transmitted to an external device including the database 400.

The output part 366 and step S317 demonstrated above are examples of the output part of the 1st compounding plan preparation part which it says in this invention, and the process by it.

As described above, according to the current stock trend state, for the supply-demand balance constraint and the property constraint, first, a formula model is set with a plan preparation time precision for a predetermined optimization period, and the set formulation plan formula model is set as an objective function. Based on the calculated year, the inventory change and the property after mixing are simulated, and the set plan confirmation period is established among the compounding plans obtained from the simulation results, and the date and time immediately after the plan confirmation period are newly formulated. By setting it as a start date and time, a series of processes which determine the mixing | blending plan for a new planning target period are repeated one by one for a predetermined number of times. In this way, a combination plan for the desired plan preparation period can be created. Thereby, the compounding plan which requires arbitrary time accuracy can be optimized at high speed and in detail, and the obtained result can be applied to actual operation as it is.

In addition, in the said embodiment, as shown in FIG. 11, a compounding plan is created every fixed period (for example, net). In addition, a constellation model may become nonlinear with respect to several constellations (alpha), (beta).

In Fig. 11, A means that the property constraint is satisfied ((Formula 14) is satisfied), and B means that the property constraint is not satisfied. That is, in the example of FIG. 11, the property violation occurred in the plural order (early and late April) with respect to the property α, and the property violation occurred in the plural order (early and late April) with respect to the property β similarly. .

In this case, if the convergence calculation described in Fig. 10 is performed separately for each order and each property, the following problem occurs. Specifically, convergence calculation is performed on constellation α in early April, convergence calculation is subsequently performed on constellation β, and convergence calculation is performed on constellation α in late April, and then convergence calculation is performed on constellation β. In doing this, the calculation process takes time.

Therefore, the convergence calculation described in FIG. 10 is performed by summarizing the order and properties of the object. For example, convergence calculations are performed on the constellations α and β at the beginning and the end of April (a slight increase in the temporary lower limit of the constellations α and β (or a small decrease in the temporary upper limit at the same time) is performed in step S403 of FIG. 10). As a result, the speed can be increased.

In addition, in the said embodiment, it demonstrated that the process of step S401 is performed again after increasing the temporary lower limit S 'by a very small amount (or reducing the temporary upper limit value by a small amount) in step S403 of FIG. In this case, the mathematical expression model in which convergence calculation is changed and there is no change in settings, specifically, the supply-demand balance model or the original linear constellation model described above is maintained. When the temporary lower limit value is increased slightly (or the temporary upper limit value is slightly reduced), and the process of step S401 is executed again, a mathematical model that changes according to the convergence calculation, specifically, a small increase of the temporary lower limit value (or the temporary upper limit value) is performed. By making the structure change only the mathematical expression model which reduced only a small amount, speed can be achieved.

In addition, as a blending plan (for example, the amount of use (mixing ratio)), a long-term plan such as an annual plan, a season plan, a monthly plan and the like is often formulated. In this way, a long-term compounding plan is prepared in advance, and the compounding plan is the standard compounding plan, and a shorter compounding plan created by the first compounding plan preparation device 100 is a certain width or more from the compounding plan that becomes the standard. It is also important to prevent it from happening.

Therefore, in addition to the objective function J constructed with respect to the costs (purchasing costs and transportation costs of the raw materials) shown in (Equation 17), the objective function constructed with respect to the formulation plan, which is a previously prepared criterion, and a condition such that it does not extend over a certain width J 'may be used. An example of the objective function J 'is shown in (formula 20).

Standard compounding ratio: Compounding ratio in blending plan to become standard

In the said example, in the monthly plan, an example at the time of making a daily blending plan as a blending plan which becomes a reference | standard as a reference | standard is shown. In this case, the thing totaled every day is minimized for every item of the difference of a compounding ratio (item, day) and a reference compounding ratio. As another example, when drafting a preliminary plan, a plan may be prepared based on the annual plan as a formulation plan. In this case, when the monthly rate determines that the compounding ratio (item, month) is determined, the sum of the difference between the compounding ratio (item and month) and the standard blending ratio for each item is minimized each month.

In addition, the formulation plan used as a reference | standard is created based on the past performance, for example, and the preparation method may be anything. Of course, a long-term plan may be prepared in advance by the blending plan preparation method to which the present invention is applied, and it may be used as a blending plan as a reference.

[Wiring plan preparation device 200]

As for the wiring plan preparation device 200, from the database 400, for example, the planned use amount of the raw material (the amount of use by the formulation plan created by the 1st formulation planning preparation device 100), the acquisition target amount, and the type of charter party contract List of vessels listed by other vessels, operation status of vessels listed in vessel list, stock situation of raw materials, purchase cost information indicating unit price of raw materials, and transportation cost information when using vessels listed in vessel list Data such as this is introduced. The wiring plan preparation device 200 creates a wiring plan for three months (nine orders), for example, based on the introduced data. Here, the order refers to a unit of a period in which the month is divided into three. Specifically, as the wiring plan, the number of ships and the linear number of ships of continuous sailing ships, irregular ships, spot ships (red port), red goods, red volume, port of call, landing bus, arrival and departure timing and spot ship to be used Determine the type of ship (size of ship defined on the basis of the maximum load of the ship).

Here, the use planned amount is the usage amount by the blending plan created by the 1st blending plan preparation device 100. The planned use amount is determined in consideration of the condition that the stock amount becomes as close as possible to the set takeover target amount and the transportation cost is made low. For this reason, when using the usage-based based on the formulation plan created by the 1st formulation plan preparation device 100 as input data of the wiring plan preparation device 200, even when making a wiring plan, it is planned without considering transportation cost. It is possible to devise a wiring plan by using a lower transportation cost than using the usage amount.

For example, there is a case where there are raw materials X and Y having almost the same properties, and in both ports (steel mills) A and B, use by the raw materials X and Y is possible. The cost of transporting raw material X to port A is 20 $ / ton, the cost of transporting raw material Y is 40 $ / ton, and the cost of transporting raw material X to port B is 40 $ / ton, and the cost of transporting raw material Y is 20 Consider the example of $ / tons. In this case, if the transportation cost is not taken into consideration when preparing the compounding plan, there is a possibility that a plan for using the raw material Y in both ports A and the raw material X in both ports B may be made. However, from the viewpoint of transportation costs, it is more preferable to plan to use raw material X in port A and raw material Y in port B. In this embodiment, the above situation can be avoided.

As shown in FIG. 1, in the wiring plan preparation apparatus 200, the code | symbol 201 is a simulator which simulated the operation | movement of a ship, a loading place, a facility in a landing place, a yard, etc. The simulator 201 receives input information determined by the macro optimizer 202 and the micro optimizer 203 described later, and executes a detailed simulation based on this. This input information includes: red port for continuous sailing ships, liners, spot ships (red port), red cargo items, lift quantity, port of call, landing buses, arrival and departure timings, number of ships to be used and the number of spot ships to be used (linear maximum load capacity) The size of the vessel defined on the basis of). The simulator is constituted by a stock trend simulator and a ship operation status trend simulator.

The stock change simulator calculates the stock change of the raw materials in each steel mill. In this stock trend simulator, the inventory trend for each item of raw materials is calculated in detail, taking into consideration the scheduled use amount of raw materials of each steel mill and the unloading time for each item of raw materials of the ship. For example, if a ship has multiple items loaded, unloads one item, and then unloads the second item, and the yard capacity has been exceeded, the inventory of raw materials on the yard decreases, leaving room for the yard capacity. There may be occasions when it is necessary to unload over time. In view of such circumstances, the stock trend is accurately simulated in response to the time of discharging.

The ship navigation trend simulator includes the estimated time of Arrival (ETA), estimated time of Berthing (ETB), and estimated time of Departure (ETD) of Red Sea ports. Calculate the trend of the ship's operational status. In this ship operation status trend simulator, in addition to the loading capacity and the landing capacity, the ship operation status is considered in detail in consideration of interference with other ships, such as whether or not the ship is present on another quay (cannot be observed if present). Simulate For example, the rider of an unloader used for discharging a ship considers the position of the hatch on which the item to be disembarked is loaded, whether or not there is a ship unloading from another bus of the same port. The ability to unload is affected by the rider of the unloader used for this unloading. As an example, in the case of unloading with one unloader, unloading can be carried out at 100% capacity at 1500 t / h. In addition, in the case of two unloaders, unloading can be performed by 70% capability at 1500 t / h * 2. The above-mentioned ship navigation situation trend simulator accurately introduces a change in the landing capability caused by conditions such as these unloader noses into a simulation. This makes it possible to formulate a specific production and logistics plan that takes into account the detailed constraints required for actual operation.

Reference numeral 202 denotes a macro optimization unit, which is the least expensive for the total amount of the plate of transportation costs, provided that it does not interfere with the steel mill's formulation plan (prepared use amount of the raw materials described above) and keeps the extraction possible. For the purpose of one, defined as the basis of the number of ships and linear (maximum load capacity of the ship) for redundant land (red port), red cargo items, red cargo volume, port order and the number of spot ships to be used for continuous sailing ships, liners and spot ships. Optimization is performed to determine the respective conditions such as the size of the vessel). The macro optimizer 202 includes a ship finance list creation unit 202a which functions as a ship finance list creation unit according to the present invention, an equation model setting unit 202b that functions as an equation model setting unit according to the present invention, and the present invention. An optimization calculation unit 202c functioning as an optimization calculation unit as described in the following is provided, and for example, nine steps are calculated with net precision.

Numeral 203 denotes a micro optimizer which optimizes the bus and the arrival / departure timing at which the total amount of the ship fee is the lowest in the plan optimized by the macro optimizer 202 to calculate an instruction to the simulator 201. do. The micro optimizer 203 includes a mathematical model setting unit 203a that functions as the mathematical model setting unit according to the present invention, and an optimization calculating unit 203b that functions as the optimization calculating unit according to the present invention. Calculate one minute with net precision.

Reference numeral 204 denotes a data introduction unit which functions as a data introduction unit according to the present invention, which is listed in the vessel list and vessel list in which vessels having different types of scheduled usage, acceptance target amount, and charter party of the raw materials are listed from the database 400. Ship operation status, raw material stock situation, raw material purchase cost, transportation cost when using the ships listed in the ship list, ship docking status at the place of shipment, loading capacity situation, facility repair and suspension schedule, at landing place Data such as ship berth status, unloading capability status, facility repair and suspension scheduled.

Numeral 205 denotes an output unit functioning as an output unit according to the present invention, which is a wiring plan created as a simulation result by the simulator 201, specifically, a red line (red port), a red line for a continuous line, an irregular line, and a spot line. Screening the stowage capacity, port of call, destination bus, arrival and departure timing and number of spot ship vessels to be used and linear (ship size defined based on the maximum load capacity of the vessel), or to an external device including a database 400 Send data.

Hereinafter, the detail of the wiring plan preparation process by the wiring plan preparation device 200 which concerns on this embodiment is demonstrated. 12 is a flowchart for explaining the steps of the respective processes in the wiring plan preparation method using the wiring plan preparation device 200. In this embodiment, a wiring plan is created for three months (nine orders) from the drafting start date set by the user as the planning preparation period.

(1) Introduction of data (step S101)

The data introduction unit 204 of the wiring plan preparation device 200 includes a ship list in which ships having different usage scheduled amounts, acceptance target amounts, and types of contracts are listed from the database 400, and ships listed in the ship list. Operation status, raw material stock situation, purchase cost of raw materials, transportation cost when using the ships listed in the ship list, ship berth status at the place of shipment, loading capacity situation, facility repair and suspension schedule, ship at landing place Introduce data such as berthing status, unloading capacity status, facility repair and suspension scheduled.

Here, the estimated use amount of raw material is information which shows the estimated use amount according to the steel mill (landing ground) in the plan preparation period, and the item of the raw material calculated in the compounding plan created by the 1st compounding plan preparation device 100. Since raw materials differ in quality, properties, etc. for each item, predetermined amounts of each item are determined and blended.

Acquisition target amount is information which shows acquisition target amount (acquisition plan amount) for each mine (shipment site) and each item. Each mine has a contract with each item about how much to buy, for example, and dividing it by the net number yields a target acquisition amount every second. It is required to wire so as to approach this acceptance target amount. However, in relation to the wiring plan, the deviation of up to tens of thousands of tons from the target acquisition amount falls within the allowable range by negotiation with the mine. In addition, depending on the contract, a contract such as not accepting a predetermined period of time for a predetermined item may be considered. Specific information about such a contract may be included in the data.

As shown in FIG. 13, the ship list is the information which lists ships from which a contract type differs, specifically, a continuous sailing ship, an irregular liner, and a spot ship. The charter party contract of a continuous sailing ship is a contract which sails continuously in a contract period. For this reason, wiring is always required (first priority). A charterer's charter party is a contract that sails only the contracted navigator or the contracted voyage in the contract period. For this reason, it is required to wire (first priority) within the contracted navigator or the contracted voyage period. The spot line is uncontracted at the time of use or execution of this embodiment. Even when the continuous sailing ship and the irregular liner are wired, the spot sailing can be requested to these spot ships when the target takeover quantity cannot be satisfied or the stock of the landing place cannot be satisfied. For the continuous sailing vessel, the charter chart (code specifying one ship), contract division, contract period (start date and end date), maximum load amount, and ship name are described in the introduction data. For non-periodships, charter codes, contract divisions, contract periods (start and end dates), contents of contracts (contracted or contracted sailing periods), maximum load and ship names are listed. These continuous and non-scheduled ships list the ships individually, but for spot ships, the ships are listed by the name of the area the ship can sail and the linearity of the ship (size of the ship defined on the basis of the maximum load of the ship). The charter code (the name and size of the area), the contract category, and the maximum payload are listed.

In addition, linear means the size of a ship defined based on the maximum load of a ship. Pmax, which represents the linearity of the spot line, is a vessel that can pass through the Panama Canal (generally this linear is called Panamax), and a Cape is a vessel that can pass through Cape Cape (generally this linear is called Cape size), VL Very Large means larger ships than these. The term "panamax" refers to a ship having a length of 900 feet or less and a width of 106 feet or less and having a maximum load capacity of 60,000 to 80,000 tons. In addition, a cape size normally refers to the ship whose maximum loadable capacity is 150,000-170,000 ton class. For spot lines, at the stage of wiring planning, the number of ships required and the linearity (ship size defined on the basis of the maximum load capacity of the ship) are determined based on the area and the size of the ship. The wiring plan is settled to a certain degree, and a procedure for negotiating with the actual ship company and contracting the ship matching the linearity is taken. For this reason, in the wiring planning stage, it is first required to determine the number of ships required and the linearity (ship size defined on the basis of the maximum load of the vessel) in the uncontracted state (the stage before negotiation with the ship company).

As shown in FIG. 14, the ship operation status is information which shows the performance and the fixed schedule of the operation status of each ship listed in the ship list. A voyage No is given by treating the ship as a voyage from shipment to disembarkation. For each voyage, like Red-Red-Yellow, Red-Yellow-Yellow, the Red and Red Ports may be one term or plural. For each vessel listed in the vessel list, the sailing No., Red Sea Dock Division, Red Sea Serial Number, Red Sea Port Code, Bus Code, Red Sea Port Arrival Date (ETA), Red Sea Landing Date (ETB), Red Sea Port Departure Date and time (ETD), the sailing time is described.

For example, the voyage No. 3 of continuous sailing ship A arrives at the coast of the port (port X1) at 20 o'clock on March 7, 2008, and the port number (x1) of the port at 20 o'clock on March 12, 2008 After paying attention to the bus indicated by "1", sailing 46920 minutes after departing the port (X1) at 20 o'clock on March 14, 2008, sailing at sea port (port B) at 10 o'clock on April 16, 2008 Arriving at the port on April 16, 2008 at 13 o'clock and paying attention to the bus indicated by the code "11" of port (port B), and sailing at port (port B) at 14 o'clock on April 18, 2008. In addition, since this vessel is a continuous sailing contract, the continuous sailing ship A sails and calls continuously in the order of red-sheep-red-sheep. That is, the continuous sailing ship A sails 20820 hours after departing the last cruise port (voyage D) of voyage No. 2 at 9:00 on February 22, 2008, and sails at No. 3 at 20 March 7, 2008. Arrive at the coast of the first red port (port X1).

When the drafting start date (starting date of target period to draft wiring plan) is the future for day to perform drafting, the stock situation of raw materials is calculated from blending plan made in the first blending plan making device 100, It is the information which shows the stock situation by each steel mill (landing ground) and item in a drafting start date. In addition, when the drafting start date is in the past with respect to the day of drafting, it is information which shows the performance stock situation by the item of the raw material which each steel mill inputted into the database 400. FIG.

The purchase cost information of the raw materials is information indicating the unit price [$ / ton (t, t)] of the raw materials for each mine (site) and for each item.

The transportation cost information is information indicating the fee for using a plate listed in the ship list and a fee for the red port according to the red port when using a ship listed in the ship list.

15 shows an example of a list of plates. As shown in FIG. 15, the charter code, the red port, 1 port, 2 port, 3 port, and plate ($ / ton) are described about each ship listed in the ship list. For example, the continuous sailing ship A has a plate of 16.00 when sailing from the ship X1 to both ports A, and a plate of 16.24 when sailing from the ship X1 to both ports B via the ship A. Also, as can be seen from the list of plates, in general, the one using a continuous sailing ship is cheaper than the one using an irregular liner or a spot ship.

16 shows an example of a list of hull fees. As shown in FIG. 16, the charter chart, the landing rate (t / Day), and the feeding / destination rate ($ / day) are described about each ship listed in the ship list. The discharging rate is the contractual capacity for discharging, which represents the amount of unloading during the day. Compared to the case where it is assumed that the cargo is unloaded by the discharging capacity, when the actual discharging time is faster, the amount set in the dispatch / delay rate can be received from the ship company. On the contrary, if the delay is delayed, the shipper will be paid the amount set for dispatch / delay rate. Despatch / Demurage Rate is a term used to refer to the contracted rate of charges for charges or returns, which occurs when Despatch and Demurage occur in red and both ports. to be. In each formula of this specification, description of a demurage rate is also used. For example, suppose that the continuous sailing ship A took 10,000 tons, and ETD 11 hours after ETA. The landing rate is 20000 (t / Day), so it will take 12 hours to take off. In this case, after 11 hours of unloading, one hour's share = 16250/24 $ of the amount prescribed by the dispatch / sustainment rate of 16250 ($ / day) is received from the ship company. On the contrary, in the case of ETD 13 hours after the ETA, the ship company pays one hour's share = 16250/24 $ of the amount prescribed by the dispatch / delay rate of 16250 ($ / day).

(2) Making of ship finance list (step S102)

The ship resource list preparation unit 202a of the macro optimizer 202 is a ship that may be the target of processing after the wiring plan or may be the target from the ship list (see FIG. 13) introduced in step S101. Select to create a ship resource list.

17 is a flowchart for explaining a vessel selection process. The ship finance list preparation unit 202a first extracts a continuous sailing ship having an undetermined portion of the scheduled flight in the planning period based on the ship list (see FIG. 13) and the ship operation situation (see FIG. 14). (Step S201). For example, suppose that a drafting plan for three months is created with a drafting start date of March 1, 2008. As shown in FIG. 14, since continuous sailing ship A is undecided after April 18, 2008, it is continuous. Nautical A is extracted.

And about the extracted continuous sailing ship A, all the patterns of the combination of the loading place and the landing place in a plan preparation period are created (step S202). At this time, specific conditions may be set based on the distance between the shipping place and the landing place, and all the patterns satisfying the conditions may be prepared. In this case, for example, a pattern or the like having an apparently inappropriate running distance can be excluded in advance, and the efficiency of the simulation can be improved. Fig. 18 creates a pattern of cruise ship A (navigation No. 4) from ship X2 and cruise ship B (navigation No. 5) from ship X2, following voyage No. 3 ("A-3" in the figure) that has already been determined. It is a figure which shows the state which it does. At the time of writing the pattern, each time is determined using standard sailing time (port distance and standard note of this ship A) or standard lifting time. For example, coast arrival time of both ports A in voyage No. 4 is [the coast arrival time of navigator X2 in navigation No. 4] + [standard shipment time] + [distance of harbor X2 and harbor A] / [Ship A's standard notebook]. Of course, since there are plural combinations of the shipping place and the landing place in the planning period for the continuous sailing ship A, a pattern of all of them (or all of the patterns meeting the above-described specific conditions) is created. The same operation is performed for other continuous sailing vessels.

Next, based on the ship list (refer FIG. 13) and the ship operating condition (refer FIG. 14), the non-scheduled ship which is available in a plan preparation period and has an undecided part is extracted (step S203). For example, as shown in FIG. 13, since the wiring scheduled year and month of the irregular line 5 are out of a plan preparation period, the irregular line 5 is not extracted. Similarly to the case of the continuous sailing vessel, for each extracted liner, all the patterns of the combination of the shipping place and the landing place in the planning preparation period (or all of the patterns matching the specific conditions) are created (step S204).

Next, based on the ship list (refer FIG. 13), the candidate of a spot ship is extracted (step S205). Specifically, first, the total acquisition target amount in the plan preparation period is calculated. Moreover, the sum total of the maximum loading amount of the continuous sailing ship and the irregular liner extracted by step S201, S202 is calculated. Thereby, the amount of transport to be replenished by the spot ship can be calculated by subtracting the sum of the maximum loads of the continuous sailing ship and the irregular ship which enters the plan preparation period from the total acquisition target amount (see FIG. 19). Based on the amount of transport to be replenished with this spot line, the number of spot lines required is calculated by referring to the maximum load of each spot line, and the minimum number of ships in each spot line is obtained. For example, if the transport volume to be replenished by the spot line is 250000 tons, four Australia-PmaxSpots are required at 250000 ÷ 75000 = 3.33, making them four candidates for the spot line contracting Australia-PmaxSpots. Similarly, two Australian-CapeSpots, one Australian-VLSpot, four Canadian-PmaxSpots, two Canadian-CapeSpots, one Canadian-VLSpot, one Australian-PmaxSpot and one Australian-CapeSpot, ... The minimum number of ships on the line is found. The minimum number of ships of the spot ship calculated | required here is the minimum number of spot ships needed when the factor is supplemented only by the spot ship of the said molten iron code. As will be described later, there may be cases where more spot lines than the minimum number of ships are required.

Next, the candidate for the spot line is extracted based on the ship list (see FIG. 13) and the ship operating situation (see FIG. 14). In this case, when there is a predetermined schedule in the ship operation situation, the vessel is extracted as a candidate for the spot ship, and the contract division of the ship list is for the plan creation period for each day set in advance for each of the non-contracted charter codes. Creates a candidate spot line. 20 shows an example of a route list of spot lines with an interval of 10 days for creating a candidate for a spot line for each molten iron code.

Here, when the number of ships created at equal intervals and the calculated minimum number of ships are compared, and the number of ships created at the same intervals is smaller, even if the candidates of all spot lines are used, the arguments satisfying the acquisition target amount are satisfied. It may be difficult to realize the quantity. For this reason, the interval which prepares a spot line candidate is narrowed so that the number of ships may become larger than the calculated minimum number of ships, and a candidate of a spot line is created. Then, similarly to the case of the continuous sailing vessel, for the candidates of each spot ship created, all the patterns of the combination of the shipping place and the landing place in the planning preparation period (or all of the combination patterns matching the specific conditions) are created (step S206). . Here, in the macro optimization described later, it is determined that each of the candidates for the spot line is used or not used, and the required linear (size of the ship defined on the basis of the maximum load capacity of the ship) and the spot line of the ship moisture are determined. do. For example, Australia-PmaxSpot-Navigation No. 3 may be planned not to be used in macro optimization after being made as a candidate.

(3) Setting the Macro Formula Model (Step S103)

The mathematical expression model setting unit 202b of the macro optimizer 202 sets a mathematical expression model constructed to represent the flight constraints of the vessel created in step S102, the supply and demand balance constraints for the raw materials at the landing place, and the target amount of restriction. The mathematical model which receives a setting is constructed (formulated) as a model based on hydraulic programming methods, such as LP (linear programming method), MIP (mixed-integer programming), and QP (secondary planning method), for example. Here, as an example, the mathematical model based on the formulation of MIP is shown. Here, the setting of the mathematical model refers to the maximum number of subscripts in each array (for example, the number of vessels) with respect to the basic mathematical model constructed in an abstract form so as to respond to changes in the number of ships, the number of harbors, or the like. , The value of the coefficient in the formula, etc. are specifically defined according to the actual plan.

First, the ship defines a variable indicating whether or not the ship is to be selected. This variable is an integer variable that takes one of the values of 1 for selecting and 0 for not selecting. Based on the value of this variable obtained by the optimization described later, it is judged whether or not to select the appropriate route.

For example, the continuous sailing ship A shown in FIG. 14 can be mentioned as a ship which is a candidate, and in voyage No. 4 ("A-4" in the figure) of this ship, the navigable ship of the said ship is X1, X2. If there are two of, the following two integer variables are defined to correspond to each enemy. Here, ETA which is the 3rd subscript of these integer variables is coastal arrival time computed by step S102.

If the call to X1 is selected as a result of the optimization, then the variable takes the following values.

In addition, when the said ship called the port of the said port, the said port, the said port order (the number which showed the number of times of both ports, for example, the port X1, the port A, the port B, the port B is the port order) Defines an integer variable indicating whether or not to select 2). That is, after the stop at the said port, when selecting to call in the said port order to the said port, this variable takes the value of 1. On the other hand, this combination takes a value of zero when such combination of redundancy, positive terms, and cruise terms is not selected. The example dealt with here shows an example which can call up to 2 double ports, but the number of double ports which can call and the number of red ports which can call can take more than that value.

In addition, the vessel defines a variable representing the amount of the item to be shipped at the vessel.

Moreover, the variable which shows the quantity which the said ship unloads the said item in the said port, the said port, and the said port order is defined.

Moreover, on the day, the variable which shows the stock amount in the said port of the said item is defined.

Constraints expressing conditions such as "loading amount of each ship not exceeding the maximum loading amount" and "loading all the loads" are built in advance as the underlying mathematical model. As will be described later, a series of processes including optimization (steps S103 to S106) and simulation (S107) can be executed repeatedly in a plurality of loops. In the optimization of the first loop, the operating constraints of the ship are set in a mathematical model based on the data introduced in step S101. In the optimization after the 2nd loop (steps S103-S107), the simulator 201 reflects the simulation result performed in the last loop, and sets a mathematical model. Here, the load amount of each ship does not exceed the maximum load amount, the load amount lands, etc. are set as a mathematical model.

The constraint that the loading amount of each ship does not exceed the maximum loading amount is represented by the following constraint (formula 21).

The constraint that the load amount is fully landed is represented by the following constraint (formula 22).

In addition, as a supply and demand balance constraint of the raw materials at the landing place, as shown in Fig. 21, a constraint condition that "the stock quantity of each item is always secured more than the safety stock quantity" is established as a mathematical model. In the optimization of the first loop, this mathematical model is set based on the data introduced in step S101, and after the next loop (steps S103 to S107), the simulation result in the simulator 201 is reflected.

First, the pharmaceutical formula which shows the change of the stock amount of each item is represented by following (equation 23). That is, the value which subtracted the stock quantity of the previous day and the quantity which lands on the day from the stock quantity of the day becomes the planned use amount of the day.

The constraint that the stock of each item is always secured more than the safety stock is represented by the following constraint (formula 24).

In addition, although the raw materials unloaded at both ports accumulate in a yard, the inventories of this unloaded raw material cannot be considered unless it is below the upper limit of a yard capacity. However, raw materials accumulated in the yard can be unloaded when the day passes, that is, when the ship is waiting. However, if the landing volume exceeds the yard ability by a certain amount, the time for the demolition will be insignificantly large. Therefore, for example, the restriction | limiting "to allow for more than about 1% of yard capacity with respect to a takeoff quantity" is formulated. This constraint is represented by the following constraint (formula 25).

In addition, with respect to the acquisition target amount constraint, the setting is performed in the first loop based on the data introduced in step S101 and after the next loop (steps S103 to S107) by reflecting the simulation result in the simulator 201. Regarding the acquisition target amount constraint, for example, the amount of optimization (shipping amount) to be optimized does not open more than a certain width from the acquisition target amount, the acceptance of the acquisition (as described above, the predetermined period is not acquired for a given item, etc.). Etc.) are built into the mathematical model. Here, in the case of considering the constraint that the takeover amount does not open more than a predetermined width from the takeover target amount, as shown in FIG. 22A, for example, simply set an upper and lower limit value for the takeover target amount at every order (or monthly), It is conceivable to make the constraint not to exceed the upper and lower limits. However, in that case, for example, if the shipment volume satisfies the lower limit but the situation continues to fall below the acquisition target amount, accumulation may occur annually, which may result in under acceptance. Therefore, as shown in Fig. 22B, the accumulation of the acquisition target amount and the accumulation of the acquisition amount are taken into consideration every time (or every month) until then, so that the difference between the accumulation of the acquisition target amount and the accumulation of the acquisition amount is reduced (minimum or not exceeding the upper and lower limits. It is appropriate to set constraints. In order to formulate the constraint, a variable representing an excess amount and an insufficient amount from the accumulation target accumulation amount of each order is defined.

In addition, a variable representing the accumulation of the acquisition amount of each order is defined.

First, a constraint expression representing the accumulation of the acquisition amount of each item is represented by the following equation (26). In other words, the cumulative amount of acquisitions is the sum of the unloading amount of the vessel (navigation) in which the ETA enters during the period from the drafting start date to the corresponding order.

A constraint expression representing the cumulative acquisition target amount, excess amount, and shortage of each item is expressed by the following equation (27). That is, from the accumulated accumulation amount, the excess amount is subtracted when the excess occurs, and when the excess occurs, the deficiency is added to coincide with the acquired accumulation amount. Here, the cumulative acquisition amount and the acquisition target accumulation amount may be said to be a good plan. That is, the less the excess amount and the insufficient amount, the better. For this reason, as described later, this excess and deficit are added as items of the objective function and minimized by optimization.

Here, in order to formulate the minimization of the total amount of plates as the objective function, an integer variable representing the order of the angular order is introduced. This call order variable is a case in which a specific vessel selects a combination of a particular port as a port, a port 1 as the first port, and a port 2 as the second port, and does not select a port order of this combination. Takes a value of any one of 0 representing.

The method of describing this logical relationship as a formula of a mixed-integer programming method is generally well known, and can be formulated as follows.

(4) Optimization based on the macro equation model and the objective function (step S104)

The optimization calculation unit 202c of the macro optimization unit 202 performs optimization calculation based on the objective function (evaluation function) constructed with respect to the transportation cost, using the mathematical model set in step S103. In the optimization calculation, the problem is solved as an optimization problem by, for example, hydraulic programming methods such as LP (linear programming), MIP (mixed constant programming), and QP (secondary planning).

In the optimization calculation here, the value of the following variable is determined using an objective function for the purpose of minimizing the total amount of plates in the transportation cost. Thereby, the linear (the size of the ship defined on the basis of the maximum load of the ship), the number of ships, the redemption site (red sea port), the red sea item, and the red sea amount which make the total amount of plates the cheapest are selected.

Here, the plate to be filled in the ship is the sum of the reference plate from the port of service to the port of claim 1 in claim 1, and the polynomial landing additional plate which is obtained when the port of claim is mentioned in another paragraph, in this case, from the first port to the second port. It is the product of the sum of the polynomial unloading additional plates that occur when the ship is called extra and the amount loaded.

For example, when the continuous sailing ship A-navigation No. 1 carries 75000 tons of load from X1 to 1st port A from FIG. 15, it becomes the reference plate 16.00, and the plate (ship use cost) is 16.00 * 75000 = 1,200,000. Becomes After stopping by A as the second cruise port, when stopping at B, the polynomial landing additional plate is (16.24-16.00) = 0.24, and the vessel use cost at this time is (16.00 + 0.24) x 7500 = 1,218,000.

From the above, if the objective function (hereinafter referred to as a macro objective function) used in macro optimization is represented by an expression, the following expression (Formula 31) is obtained.

Here, macro optimization also aims at reducing the difference between the acquisition target amount accumulation and the acquisition amount accumulation in consideration of accumulation of the acquisition target amount and acquisition amount. For this reason, an item is added to the objective function that minimizes the sum of the excess amount and the lack amount from the accumulation target amount of each order. For this reason, (Formula 31) representing the objective function is changed to the following (Formula 32).

Macro optimization optimizes the problem of molten iron as a whole.

Although the construction of the objective function has been described with respect to the plate, the objective function may be used for the purpose of minimizing the total amount of the plate and the total amount of the purchase cost of the raw materials. As described above, the acquisition target amount of the raw materials is determined by the contract, and there is no significant change in the purchase cost of the raw materials, but among them, the total amount of the purchase cost of the raw materials can be minimized.

As described in the above items (3) and (4), the expression to be minimized is formulated as a constraint and each expression to be satisfied. The above constraints are represented by linear equations or inequalities, and the objective functions described above are represented by linear equations. In addition, a mathematical model and an objective function are constructed as models in which variables to be integers exist. The problem formulated in this way is generally well known as a mixed constant planning problem, and this problem can be (analytically) optimized.

In macro optimization, time precision is calculated as net precision. The optimization period is set to nine orders in the first loop (steps S103 to S107), eight orders in the next loop (steps S103 to S107), and one order in the last loop (steps S103 to S107). The time precision is calculated as the net precision. The first one of the optimization periods (from 9 to 1) is used as the plan confirmation period, and the calculation result in the plan confirmation period is output to the micro optimizer 203.

(5) Setting the micro equation model (step S105)

The formula model setting unit 203a of the micro-optimizing unit 203 is a balance between supply and demand of raw materials at the ship's limitation and the landing place, among the ship's operating constraints in the wiring plan of the plan determination period determined by the macro optimizer 202. Sets the mathematical model that represents the constraint. The mathematical model used here is constructed according to hydraulic programming methods, such as LP (linear programming method), MIP (mixed-integer programming), and QP (secondary planning method). Here, as an example, the mathematical model based on the formulation of MIP is shown.

By macro optimization, both terms to call are determined. Here, a plurality of buses (barriers) exist in both ports for the ship to pay attention to. Therefore, a variable for selecting which bus in the ports is concerned is defined. This variable is an integer variable which takes the value of either 1 for selecting the bus and 0 for not selecting the bus.

In addition, a variable representing a time (ETA) at which the vessel starts coastal waiting for attention to the bus is defined. Since the time cannot be directly defined as a variable for formulation in the MIP, it is defined as the elapsed time from the drafting start date. That is, when the drafting start date is 0: 0 on January 1 and the ETA is 1:10 on January 1, it is defined as taking a value of 70. In addition, this variable is defined as a variable that takes a continuous value, not an integer variable.

Similarly, we define a variable that represents the ETB.

Similarly, we define a variable that represents the ETD.

Moreover, the variable which shows the stock amount of the said minute and the said item in the said both ports is defined.

The ship's hull constraint is also set based on the data introduced in step S101 in the first loop, and after the next loop (steps S103 to S107), the simulation result in the simulator 201 is reflected. Regarding the ship's hull restrictions, ship operating conditions (ETB> ETA, ETD> ETB + unloading time, etc.) at both ports, bus conditions (LOA (full length), DRAFT (full depth), BEAM (full width) allowed) , Redemption ability, yard ability, etc.] are constructed as a mathematical model. Here, these mathematical models are set.

The ship whose port was determined by macro optimization needs to pay attention to either bus of the said port. For this reason, this restriction | limiting is represented by the following constraint (formula 33). That is, for the vessel, one bus must be selected (the value of the variable is 1) from among the conceivable buses.

The ETB needs to be after the ETA. This constraint is represented by the following constraint (formula 34).

The ETD needs to be after the ETB + unloading time. Here, since the amount of discharging on the bus is determined by macro optimization, the discharging time on the bus becomes the discharging time = the discharging amount / landing capacity using the standard discharging capacity on the bus. In view of the above, the constraint is represented by the following formula (formula 35).

In addition, the supply and demand balance constraints of the raw materials at the landing site, similar to the macro optimization described above, are also used in the micro optimization (steps S105 to S107). This supply and demand balance constraint is also set based on the data introduced in step S101 in the micro optimization of the first loop, and reflects the simulation result in the simulator 201 in the micro optimization after the next loop. Also in micro optimization, a mathematical formula model constructed to show the constraint that "the stock amount of each item is always secured more than the safe stock amount" as shown in FIG. 21 is set. However, in micro optimization, the time precision used is different from macro optimization. For this reason, the restriction | limiting condition used here becomes "the value which subtracted the quantity of inventory 1 minute ago and the quantity landed at the said time from the quantity of inventories at that time is the estimated use amount for the said minute."

In addition, although the raw materials landed at both ports accumulate in a yard, the inventories of this landed raw material cannot be conceived unless they are below the upper limit of the yard capacity. In other words, the inventory at the time of ETB needs to be below the upper yard capacity. This constraint is represented by the following constraint (formula 37).

(6) Optimization based on the micro equation model and the objective function (step S106)

The optimization calculation unit 203b of the micro optimization unit 203 performs optimization calculation based on the objective function (evaluation function) constructed with respect to the transportation cost, using the mathematical model set in step S105. At the time of optimization calculation, a problem is solved as an optimization problem by hydraulic programming methods, such as LP (linear programming), MIP (mixed-integer programming), and QP (secondary programming), for example.

In the optimization calculation here, the objective function aimed at minimizing the total sum of the hull charges is used, δ (ship, bus) indicating that the ship is not on / off, ETA (ship, bus), ETB indicating the ETA time. Variables such as ETB (ship, bus) representing the time and ETD (ship, bus) representing the time are determined. As a result, the bus and the arrival / departure timing that select the lowest transportation cost are selected.

Here, the cost of the ship to be incurred by the ship is compared to the ETD-ETA and the contracted standard anchoring time, and when the anchoring is longer than the standard anchoring time, that is, ETD-ETA > In the opposite case, you will receive the contracted cost as an outgoing / discharge rate. The base anchoring time is calculated as the land quantity / landing rate using the landing rate, which is a contractually set landing capacity. For example, when continuous sailing ship A-Ship No. 1 lands 10,000 tons at both ports and takes 11 hours from ETA to ETD, it is 1 hour faster than the standard anchorage time = 10000/20000 = 0.5 days and 12 hours. In this case, the shipbuilder will receive an amount of 16250/24, which is set as a draw / sustain rate. From the above, if the objective function (hereinafter referred to as the micro objective function) used in the micro optimization is represented by an equation, the following equation (38) is obtained.

Although the constant part is included in the above formula, the constant part does not affect the minimization, so the following equation (39) becomes the objective function.

As described in the above items (5) and (6), the expression to be minimized is formulated as a constraint and each expression to be satisfied. The above constraints are represented by linear or inequalities, and the objective functions described above are represented by linear equations. In addition, a mathematical model and an objective function are constructed as models in which variables to be integers exist. The problem formulated in this way is generally well known as a mixed constant planning problem, and this problem can be (analytically) optimized.

In micro optimization, the optimization period is 10 days (one order), and the time precision is calculated as minute precision.

(7) Simulation (step S107)

The simulator 201 executes a simulation based on the solution to the mathematical model obtained by the micro optimizer 203 to determine the wiring plan for the planning decision period (one order). The time precision of the simulation is minute precision. In this simulation, by including the constraints that cannot be included in the macro equation model, the micro equation model, and the like, it is possible to create a wiring plan that takes into account the detailed constraints actually required.

For example, as an example of a constraint that is difficult to handle in macro / micro optimization, there is an unloader nose used for discharging of a single ship. The nose changes depending on the location of the hatch on which the items to be unloaded are loaded, whether or not there are ships being unloaded from other buses of the same port. The landing ability changes depending on the rider of the unloader used for this landing. For example, a situation such as "when unloading with one plane is lowered to 100% capacity at 1500 t / h" or "when two planes are lowered to 70% capacity at 1500 t / h x 2" can be exemplified. Since macro-micro optimization does not take into account these unloader radix, the simulator calculates the time calculated by the optimization to the unloader radix by simulating and accurately simulates the deviation of optimization time by introducing into the simulation. It is possible to formulate production and logistics plans that take into account the detailed constraints required for operation.

In the simulator 201, when the micro optimizer 203 adjusts the time due to the replacement of the ship's entry / exit timing or the like, the time is corrected by reflecting it in a sudden manner. Particularly, in a continuous sailing ship, if any time adjustment is made, the subsequent sailing will also be affected, so that the time is corrected in the simulator 201 and reflected in the subsequent processing by the macro optimizer 202. Doing.

(8) Update (step S109) of drafting start date

In step S108, it is determined whether the plan for the plan creation period [3 months (9 orders)] has been confirmed. If it is not yet determined, the first day of the next order of the order in which the plan is confirmed, for example, if the N order is confirmed, the first day of the N + 1 order is updated as the draft update date (step S109), and the process returns to step S103. In the next loop to be started from step S103, the stock trend in the order (N order) and the ship's operating status in the order (N order) in which the plan was confirmed are updated, and the next order (N + 1 order) is confirmed. By repeating this, the plan for the planning period (three months) is confirmed (see FIG. 23).

(9) Output of wiring plan (step S110)

The wiring plan created as described above is displayed on a monitor (not shown) by the output unit 205 or data is transmitted to an external device including the database 400.

As described above, the macro optimizer 202 and the micro optimizer 203 first set a mathematical model based on an initial value (initial condition) obtained from the input data or the entire loop, and perform optimization calculation. An instruction to the simulator 201 is calculated. When the simulator 201 finishes the simulation for the planned settlement period (one order), the macro optimization unit 202 and the microcomputer provide information on the stock trend of the raw materials in the final state of the planned settlement period and the change of the ship's operation status. To the optimizer 203. The macro optimizer 202 and the micro optimizer 203 set a mathematical model based on the given information, perform optimization calculations, and calculate instructions for the simulator. By linking the simulator 201 and the optimization units 202 and 203 in this manner, a wiring plan for a planning preparation period (three months (nine orders)) can be prepared.

According to the wiring plan preparation device (method) according to the present embodiment, the simulator 201 (inventory trend simulator, ship) calculates instructions based on the results of optimization calculations performed by the macro optimizer 202 and the micro optimizer 203. To the flight status trend simulator). Thus, since the simulation is performed based on the result of the optimization calculation, it is possible to reliably obtain the theoretical optimal solution. As a result, it is not necessary to repeatedly evaluate the simulation results and execute the simulation several times as in the prior art, so that the simulation results can be produced quickly and with high accuracy.

In addition, even when the scale of the simulator 201 is very large or when the constraints are very large and complicated, only the important part of the constraints described in the simulator 201 having a large influence on the creation of the wiring plan is introduced into the mathematical model. The scales of the model setting units 202b and 103a can be set in an appropriate range so that optimization calculation can be performed within practical time. Since the simulator 201 can describe all the restrictions to be considered, the wiring plan created by executing one simulation is guaranteed to be practically executable.

In addition, when making a wiring plan, items transported from a distant place such as Brazil may be received only once every two months or three months. Therefore, it is necessary to make a wiring plan in consideration of the long term. On the other hand, items that are frequently transported, such as China, are also returned items in a few days. In addition, management of the bus may incur a ship fee and may be performed in minutes. Therefore, planning of minute precision is required. For these demands, the macro optimizer 202 selects linearity (size of the vessel defined on the basis of the maximum load of the vessel), the number of vessels, the redemption site (the red port), the red line item, the red volume, the port of call, The micro-optimizing unit 203 shared the calculations so as to select the use bus and the arrival and departure timing. For this reason, load can be suppressed and it can be calculated | required with high precision. In other words, macro optimization and micro optimization can be linked and executed repeatedly, taking into consideration the available ships, redundancies, items, and quantities that need to be specified for a long time (for example, 3 months) for a long time, while providing detailed time accuracy. The use of buses and arrival / departure timings required by the system makes it possible to optimize the short-term (fine) time accuracy.

In addition, when making a wiring plan, you may make it possible for a user to individually fix linear (the size of a ship defined based on the maximum load of a ship), the number of ships, the red port (red boat port), a red cargo item, and a red cargo quantity. . For example, there are circumstances in which it is predetermined to use a predetermined vessel or to use a predetermined enemy port. In particular, after the wiring plan is drawn up based on the amount set as the acquisition target amount, negotiation with the mine proceeds and the acceptance amount is determined. Not allowed. However, with regard to the landing place, there is a lot of room for changing the landing place, the landed item, and the landing amount by judging the stock situation. For this reason, when the operation which can fix | immobilize a shipment place (shipping port), a shipment item, and a shipment quantity collectively is attained, convenience for a user becomes high.

In addition, the wiring plan preparation method described so far has described an example in which the optimization calculation is performed based on the objective function (evaluation function) constructed with respect to the transportation cost in the optimization calculation unit 202c of the macro optimizer 202. You may add other objective functions.

For example, in order to level the load at the loading site, avoid the arrival of ships entering and leaving the same place of shipment at the same time, or conversely continuing the period of non-shipping at the same place, i.e. as evenly as possible during the planning period at the same place of loading. Wiring is required.

Therefore, as shown in FIG. 24, the acquisition quantity of all the items for every shipment place is aggregated in net unit (or monthly unit), and the accumulation until then is considered (acquisition quantity accumulation). Moreover, the acquisition target amount of all the items is aggregated in net unit (or monthly unit) for every shipment place, and the accumulation until then is set as a target value (acquisition target amount accumulation). And we construct an objective function aimed at minimizing the difference between the accumulation of arguments and the accumulation of argument targets.

As a result, the takeover amount of the shipping destination is equally close in each order (or each month), that is, even wiring becomes possible.

Similarly, in order to equalize the load on the landings, it is avoided that ships entering and leaving the same landings are concentrated at the same time or, conversely, that the periods during which the ships do not enter and exit continue, i.e. wiring as evenly as possible during the planning period at the same landings. It is required.

Therefore, as shown in FIG. 25, the amount of unloading of all the items for each landed destination is aggregated in net unit (or monthly unit), and the accumulation up to that time is considered (landing quantity accumulation). In addition, for each landing place, the standard landing capacity is counted in net units (or monthly units), and the accumulation up to that time is set as a target value (the landing site standard landing capacity accumulation). We define the car as the residual land quantity and build an objective function aimed at minimizing the residual quantity.

As a result, the unloading amount of the landing place is equally close in each order (or each month), that is, even wiring is possible. In other words, the body line can be suppressed also in macro optimization.

As described above, it becomes possible to collectively create a blending plan for receiving and mixing a plurality of raw materials and a wiring plan for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites. In addition, in these plans, it becomes possible to minimize transportation cost as a whole through a compounding plan and a wiring plan.

(2nd embodiment)

As 2nd Embodiment, the example which introduces the 2nd formulation plan preparation device 300 is demonstrated. Based on the wiring plan created by the wiring plan preparation device 200, the 2nd formulation planning preparation device 300 prepares the formulation plan which receives and mixes several compounding raw materials. In addition, the structure and basic process operation | movement of the 2nd compounding plan preparation apparatus 300 are the same as that of the 1st compounding plan preparation apparatus 100, and it demonstrates here also with reference to FIGS.

FIG. 2: is a figure which shows the example of the system structure containing the 2nd compounding plan preparation apparatus 300. As shown in FIG. As illustrated in FIG. 2, when the second formulation planning preparation device 300 creates a formulation plan, an operator sets data of the following constraints and prerequisites required for drafting a formulation plan, Or purchase which shows plan making period to introduce from database 400, arrival plan of raw materials (amount of stock by wiring plan created by wiring plan making apparatus 200), stock situation of raw materials, property of raw materials, unit price of raw materials Cost information, transportation cost information when using the ship.

The second blending plan preparation device 300 executes simulation to create a blending plan in which a variety of raw materials are received and mixed. This mixing plan includes the usage amount (mixing ratio) of each item that satisfies the supply and demand balance constraints of the raw materials and the property constraints after mixing. In the second blending plan preparation device 300, as described later, the supply and demand balance constraints of the raw materials constructed in accordance with the repair planning methods such as LP (linear planning method), MIP (mixed water purification planning method), and QP (secondary planning method) A formula model (also referred to as a "supply and balance model") and a mathematical model (also referred to as a "formula model") indicating the property constraints after mixing are set and calculated according to the conditions, thereby optimizing the formulation plan.

Here, in the 1st compounding plan preparation apparatus 100, as for the arrival amount, the formulation plan was created so that the accumulation amount of the arrival amount does not deviate significantly from the acquisition target accumulation amount. However, in the 2nd mix plan preparation device 300, since the amount of stock is previously determined as the amount of unloading for every ship by the wiring plan preparation device 200, it becomes the quantity already known. For this reason, in the 2nd compounding plan preparation device 300, the amount of stock is not a quantity calculated | required but a fixed quantity. In addition, it is not necessary to consider the acquisition target amount for the above reason.

In addition, in 1st Embodiment, the wiring plan is created using the usage plan created by the 1st compounding plan preparation device 100 as input data of the wiring plan preparation device 200. In this case, in the 1st compounding plan preparation apparatus 100, the plan is created based on the acquisition target accumulation amount. At this time, for example, consider a case where the target accumulation amount is set to 50,000 tons for the raw material X, and 50,000 tons equal to the acquisition target accumulation amount are planned as the accumulation amount for both the use plan and the arrival plan. When the usage plan is used as input data of the wiring plan preparation device, when there is only one ship having a maximum loading capacity of 450,000 tons registered in the ship list, the loading amount is 4.50,000 tons, and the stock is insufficient as follows. Is likely to generate

Inventory = 40,000 tons-50,000 tons = -500,000 tons

Although the above example is an extreme example, in the first compounding plan preparation device 100, a compounding plan is created based on the acceptance target amount, and a wiring plan is created based on the created use plan. If the maximum payloads do not match, the same phenomenon as the above example may occur.

Therefore, in order to create a better formulation plan, the formulation plan is corrected by the second formulation plan preparation device 300 by using the wiring plan determined by the wiring plan preparation device 100, which is not an acquisition target amount, as input data. . Thereby, it becomes possible to prevent the possibility of inventory shortage which arises because the subtle acquisition target amount and the maximum loading amount of a ship as mentioned above do not match.

In this embodiment, although the fare of a ship is considered, the stock change of the wiring plan side uses the usage quantity planned by the 1st compounding plan creation apparatus based on the acquisition target quantity, without taking into consideration the detailed operation situation, such as the time of arrival at the bus. The blending plan can be updated again, taking into account the detailed wiring conditions that appear in the results of the simulation by the simulator and the ship operation status trend simulator. This effect brings about a great effect on the improvement of the accuracy of a compounding plan.

The display unit 303 displays the amount of use (compound ratio), the amount of stock received, the stock trend graph, and various documents of each item determined by the second formulation planning preparation device 300.

The supplier evaluation unit 304 evaluates the obtained compounding plan from various viewpoints (for example, inventory trends, properties, etc.), and corrects the compounding ratio or the like as necessary if it is not satisfactory. At that time, if necessary, the weight of the objective function and the index of the evaluation are changed, or the target period and plan determination period for setting the mathematical model are changed. In addition, it is possible to set a mathematical model that reflects the intention of the operator, such as fixing the amount of use of all or designated processing. And the 2nd formulation plan preparation device 300 recreates a formulation plan again.

3 is a block diagram showing a basic configuration of a second compounding plan preparation device. As shown in FIG. 3, the second blending plan preparation device 300 includes a simulator (including a stock development simulator 311 and a constellation simulator 312) and a model functioning as a mathematical model setting unit according to the present invention. It includes a setting unit (supply / demand balance model setting unit 313, constellation model setting unit 314), and a planning unit 315 functioning as an optimization calculation unit according to the present invention, and also has an input / output unit.

The stock trend simulator 311 is a simulator for calculating the supply / demand state (stock trend) of each raw material. The property simulator 312 is a simulator for calculating the property after mixing raw materials. The inventory trend simulator 311 and the property simulator 312 interlock with each other, and calculate the stock trend of raw materials and the property after mixing.

In the present embodiment, the input includes, for example, a plan preparation period, a stock schedule of raw materials, a stock situation of raw materials, properties of raw materials, purchase cost information indicating a unit price of raw materials, transport cost information when using a ship, and the like. Based on the data 316, a setting process of the mathematical model is performed. Based on the pre-set time precision for the optimization period set in advance from the drafting start date of a blending plan, the hydraulic constant planning methods, such as LP (linear programming method), MIP (mixed-integer constant planning method), and QP (secondary planning method), etc. In accordance with the above, the mathematical expression model indicating the supply and demand balance constraints (stock constraints) is set by the supply and demand balance model setting unit 313, and the mathematical expression model indicating the property constraints is set by the property model setting unit 314.

By using the formula model set by the supply / demand balance model setting unit 313 and the property model setting unit 314, it is possible not to drop the inventory, satisfying the required properties, and furthermore, the cost (purchasing cost and transportation cost of raw materials). Optimization calculation is performed by the planning unit 315 so as to minimize the size of the combination plan. Based on the results of this optimization calculation, calculation instructions for the stock trend simulator 311 and the property simulator 312 are calculated. In response to this calculation instruction, the stock trend simulator 311 simulates the stock trend, and the property simulator 312 simulates the properties of the products and semi-finished products manufactured according to the plan. For example, in the steel industry, properties such as coke (product) obtained by mixing and solidifying coal and solidifying slab (semi-finished product) of solidified molten steel obtained by reducing iron ore are simulated.

According to the second formulation planning preparation device 300, the calculation instruction based on the result of the optimization calculation performed by the planning unit 315 is not performed based on a predetermined rule as in the prior art, but it is a stock transition simulator. 311, and outputs to the constellation simulator 312. For this reason, it becomes possible to reliably perform the optimal calculation instruction according to the idea at that time.

For example, as shown in FIG. 7, the simulation by the stock trend simulator 311 and the property simulator 312 is performed about predetermined plan confirmation period. When the simulation is completed, the drafting start date is updated, and the supply-demand balance model setting unit for the new optimization period is based on the final state of the plan-determination period before the update, that is, the inventory trend at the drafting start date after the update and the property information. 313 sets a mathematical model indicating the stock constraint, and a constellation model setting section 314 sets a mathematical model showing the constellation constraint and gives it to the planning unit 315. When the stock trend and the constellation information are provided, the planning unit 315 performs optimization calculation.

Also in the 2nd compounding plan preparation apparatus 300, as described in 1st Embodiment, a simulator (stock change simulator 311, the property simulator 312) and a model setting part (supply balance model setting part 313) , The constellation model setting unit 314] and the planning unit 315 are linked to create a formulation plan. As a result, the following effects are obtained. (1) A formulation plan can be created without repeating the simulation. (2) It is possible to shorten the calculation time by introducing only the important part having a large influence on the formulation planning, and (3) solve a large-scale problem.

Hereinafter, each step of the structure of the 2nd formulation plan preparation apparatus 300 and the formulation plan preparation method performed using this apparatus is demonstrated in detail. FIG. 4: is a figure which shows the detailed structure of the formulation planning preparation apparatus with respect to the basic structure of the 2nd formulation planning preparation apparatus 300 demonstrated using FIG. 5 is a flowchart which shows each step of the formulation planning preparation method performed using this apparatus.

As an outline of formulation planning, for example, as shown in FIG. 6, balancing supply and demand of raw materials (items) in a plurality of steelworks (both ports) a to c, (do not drop inventory of each item A to N). To satisfy the required properties, to minimize costs (purchasing costs and transportation costs of raw materials), and to use the amount of each item A to N per steel mill a to c as a formulation plan that satisfies the above conditions. Compounding ratio), and calculation and adjustment processes such as determining the amount of stock. Here, the predetermined usage amount which is the total amount of the usage amount per steel mill is given as input data. For this reason, it becomes a compounding ratio (%) = consumption / anticipated usage amount x100. For this reason, when one of usage-amount and a compounding ratio is determined, the other will be determined.

(1) Introduction of input data (input data introduction unit 351 of FIG. 4, step S301 of FIG. 5)

The information necessary for this processing (receipt schedule of raw materials, stock situation of raw materials, properties of raw materials, purchase cost information indicating unit cost of raw materials, transportation cost information when using a ship), etc. Make corrections.

Here, the arrival schedule of the raw materials introduced by the input data introduction unit 351 includes a wiring plan (shipping point for each ship, arrival date and time of arrival, shipping item, quantity of shipment, port of arrival, port arrival date, landing item, and landing amount). Information indicating the amount of arrival, such as planning), is included. For example, in the wiring plan shown in FIG. 26, the operation schedule of each ship listed in the ship list as shown in FIG. 13 is arranged. In the wiring plan, a plan is drawn up for the items listed on the ship list, including items including ship port, port arrival date, item, shipment volume, port port, port arrival date, item, and land quantity.

For example, in the wiring plan shown in FIG. 26, the sailing No. 1 of the continuous sailing ship A arrives at the coast of the red port (port X1) at 21 o'clock on November 19, 2007, and at 21 o'clock on December 13, 2007. We pay attention to bus represented by red port (port X1) code "1" and depart port (X1) at 21:00 on December 14, 2007. At this time, load 400,000 tons of item A and 35000 tons of item B. After that, we sailed for 16980 minutes and arrived at the port of Port A (port A) at 16:00 on December 26, 2007, and arrived at the bus indicated by code "4" of port (Port A) at 1:00 on December 27, 2007. We depart and depart both ports (section A) at 16:00 on December 28, 2007. At this time, unload 25,000 tons of item A and 15000 tons of item B. After that, we sailed for 3060 minutes and arrived at the port of port (port B) at 19:00 on December 30, 2007, and arrived at the bus indicated by code "13" of port (port B) at 19:00 on December 30, 2007. We depart and depart both port (section B) on January 1, 2008 at 23:00. At this time, unload 15,000 tons of item A and 20,000 tons of item B. In voyage No. 1 of the continuous sailing vessel A exemplified above, on December 27, 2007, the item A of the raw material is 25,000 tons, the item B is 15000 ton, and the port B (paragraph B) 12 December 2007. It becomes input data of the formulation planning preparation apparatus that 15,000 tons of item A of a raw material and 20,000 tons of item B were received on the month 30.

The purchase cost information indicating the stock situation of the raw materials, the properties of the raw materials, and the unit price of the raw materials is the same as in the case of the first formulation planning preparation device 100 described in the first embodiment.

In addition, about the transportation cost information at the time of using a ship, the wiring plan planned in the future is transmitted to input form 2 by the wiring plan preparation device 200 as the input data. For this reason, it is not necessary to use the predicted plate by item and port, and the plate by ship, port, and port can be used.

The input data introduction part 351 and step S301 demonstrated above are examples of the data introduction part of the 2nd compounding plan preparation part which it says in this invention, and the process by it.

(2) Setting of compounding plan preparation period (plan preparation period setting part 352 of FIG. 4, step S302 of FIG. 5)

Set a period of time to develop a formulation plan. This preparation period allows setting any period according to the needs of the planner. Here, for example, 10 days are drawn up.

(3) Setting of the compounding plan preparation time precision (time precision setting unit 353 of FIG. 4, step S303 of FIG. 5)

Set the time precision and simulation precision for creating a formulation plan. This time precision and simulation precision allow arbitrary accuracy to be set individually according to the needs of the planner. For example, in the first half of the planning period that requires detailed precision of the drafting, the precision is strict, and the roughness is not so strict in the second half of the planning period. Efficient planning is possible.

(4) Setting of the optimization period (optimization period setting unit 354 in FIG. 4, step S304 in FIG. 5)

Set an optimization period to create a formulation plan. This optimization period makes it possible to set any target period individually according to the needs of the planner. Here, as an example, the optimization period is three days through the plan preparation period.

(5) Setting of plan confirmation period (plan confirmation period setting part 355 of FIG. 4, step S305 of FIG. 5)

Set a plan confirmation period to finalize the formulation plan. This plan determination period enables the arbitrary period to be set individually according to the needs of the planner. For example, the planning confirmation period is shortened in the first half of the planning period that requires detailed precision in the drafting, and the planning confirmation period is extended in the second half of the planning period that is sufficient by only rough planning. This enables efficient plan creation with a short calculation time while having sufficient precision. Here, as an example, the plan determination period is set to one day. In this case, about the compounding plan obtained as a result of the simulation based on the solution to a mathematical formula model, the 1st day is decided through a plan preparation period.

(6) Set supply and demand balance constraints of the formulation plan as a mathematical model (supply and balance model setting unit 313 of FIG. 3, supply and demand balance model setting unit 356 of FIG. 4, step S306 of FIG. 5)

On the basis of all or part of the data introduced by the input data introduction unit 351, the set optimization period is set based on the supply and demand balance constraints at the set time precision.

Similarly to the case of the first formulation planning preparation device 100, the inventory amount of each item is required to be equal to or greater than a value called a constant safety inventory amount. Restriction in this case is represented by said Formula (4).

In addition, the stock amount of each item is determined from the stock amount of the previous day, the stock amount of the previous day, and the usage amount of the previous day. Constraints representing the relational expression in this case are represented by the above-described formula (5). That is, the stock amount of the day becomes the value which subtracted the consumption amount of the day from the value which added the stock quantity of the previous day and the quantity received (unloaded) on the day.

In addition, the total of the days with which each item is used needs to correspond with the usage-amount scheduled with respect to the total of all the items of the day. The constraint expression which shows the relationship in this case is represented by said (formula 6).

In addition, in view of factors such as the purchase of various raw materials, an operator sets a target blending ratio and requires that a blending plan for realizing a blending ratio close to the target blending ratio given thereto is created. In other words, when the blending ratio is far from the assumption of the operator, it is assumed that the estimated purchase amount cannot be satisfied, the purchase amount is exceeded, or the operation equipment is subjected to unreasonable operation. For this reason, it is necessary to output the compounding ratio near the compounding ratio provided as a target. Constraints for realizing the above functions are shown below. That is, the value which subtracted the use target amount (targeting compounding ratio) (constant) from the usage amount of an item is defined as a variable of the excess amount from a use target amount. Here, since the closer the usage amount and the usage target amount are, the better the plan is, the smaller the excess amount is. For this reason, as described below, this excess is added as an item of the objective function and minimized by optimization. Similarly, the value obtained by subtracting the use amount from the use amount of the item is defined as a variable of the shortage from the use amount. Here, the usage amount and the usage target amount are better plans that take a closer amount, so the smaller the shortage, the better. For this reason, as described below, this lack is added as an item of the objective function and minimized by optimization. In this case, the constraints representing the relationship between the amount of use, the target amount of use, the amount of excess, and the amount of deficiency are expressed by the above-mentioned formula (7). In other words, when an excess occurs, the excess amount is subtracted from the amount used, and when a shortage occurs, the amount is insufficient to coincide with the use target amount.

Moreover, when the compounding ratio of the previous day and the compounding ratio of the next day largely differ, it will cause difficulty in operation. That is, it increases the preparation time for using other raw materials or causes a malfunction of the equipment. For this reason, it is demanded that the compounding plan which the compounding ratio of the previous day and the compounding ratio of the following day does not differ greatly is created. Constraints for realizing this are shown in the above expression (9).

In addition, the supply-demand balance constraint mentioned above is an example, You may change into another constraint or add another constraint.

(7) A mathematical model is set using the constellation constraint of the compounding plan (the constellation model setting unit 357 of FIG. 3, the constellation model setting unit 357 including the linearization unit 357a of FIG. 4, and the steps of FIG. 5). S307, S307a]

Based on all or a part of the data introduced by the input data introduction unit 351, a mathematical expression model is set using the constellation constraint using the set optimization period and time precision. When preparing the mixing plan of iron ore, examples of the properties of the raw materials used as properties include iron powder, SiO ₂ , Al ₂ O ₃ , SiO ₂ , and the like. Examples of the properties in the case of preparing a coal blending plan include CSR (strength after hot reaction), DI (coke strength), VM (volatile content), expansion pressure, and the like. These properties need to satisfy the required property constraints. An example of the property model after mixing was shown to said (formula 14). In addition, although the example which has a lower limit S is shown in (Formula 14), when it has an upper limit, there may be a case where it has both an upper limit and a lower limit.

Here, for many constellations, the formula f (x _A , x _B , x _C ,..., X _N ) included in the constellation model is linear with respect to the blending ratio, as shown in the above formula (15). do. For example, with respect to SiO ₂ , when the blending ratio of item A is 40%, the SiO ₂ component of item A is 1%, the blending ratio of item B is 60%, and the SiO ₂ component is 2%, The properties of the SiO ₂ component after mixing are 1 × 0.4 + 2 × 0.6 = 1.6%.

By the way, depending on the property, the expression f (x _A , x _B , x _C , ..., x _N ) representing the property may be nonlinear. In this case, as described below, in the linearization unit 357a, the linear equation f '(x _A , x instead of the nonlinear equation f (x _A , x _B , x _C ,..., X _N ) is used. _B , x _C ,..., X _N ) are introduced to form a mathematical model.

The processing in the linearization unit 357a will be described. If the formula f (x _A , x _B , x _C ,... X _N ) representing a constellation is nonlinear, the linear formula f '(x _A , x _B , x _C ,... x _N ) is introduced. Formula of linear f '(x _A, x _B, x _C, and and and, x _N), the formula for the non-linearity f forming the lower limit of (x _A, x _B, x _C, and and and, x _N) Consider that the relationship of the above expression (16) is established. In addition, Equation 16 does not always need to be established, but may be established within a required range.

For example, as the linear expression f '(x _A , x _B , x _C ,..., X _N ), the weighted average represented by the above-described formula (17) is considered. The weighted average is a value obtained by calculating the properties when 100% of a single item is used from the nonlinear formula f (x _A , x _B , x _C , ..., x _N ), multiplying the compounding ratio, and adding the used items. .

In order to simplify the explanation, an example in which the blending ratio of Item A is 90% and the blending ratio of Item C is 10% is considered. In this case, the weighted average of the linear expression f '(90, 0, 10, ..., 0) is represented by the following formula.

f '(90, 0, 10, ..., 0)

= 0.9 x f (100, 0, ..., 0) + 0.1 x f (0, 0, 100, ... 0)

If the weighted average satisfies (Equation 16) from past results, the weighted average can be used as a linear equation f '(x _A , x _B , x _C , ..., x _N ). have. In other words, if weighted average? Is regarded as a constraint, it is assumed that (Equation 14) is established, and thus the possibility of formulation can be obtained.

In the linearization unit 357a, as shown in the above formula (14) ', the nonlinear formula f is a lower limit for the linear formula f' (x _A , x _B , x _C , ..., x _N ). The mathematical model is set by setting a temporary lower limit S '= S-s (s: offset value) smaller than the lower limit S for (x _A , x _B , x _C ,..., x _N ).

As mentioned above, the case where the property constraint after mixing has a lower limit was demonstrated to the example. In addition, the above-mentioned property constraints are an example, and you may change into another constraint (including the case where the property constraint after mixing has an upper limit), and may add another constraint.

The supply and demand balance model setting unit 356 (supply and balance model setting unit 313) described above and step S306 and the constellation model setting unit 357 (the constellation model setting unit 314 in FIG. 3), and steps S307 and S307a, It is a mathematical expression model setting part and the processing example by that of the 2nd compounding plan creation part which are said to this invention.

(8) Immobilized Extraction Processing (Fixed Extraction Processing Unit 358 of FIG. 4, Step S308 of FIG. 5)

As shown in FIG. 9, the fixed, that is, unchangeable among the ship's port, shipment item, shipment amount, boat port, landing item, and landing amount which are the items of a wiring plan are extracted. In the case where "shipping port" and "shipment goods" are immobilized for each charter under the conditions given in advance, a plate for each ship, for each ship, for each port (see Fig. 15) is used. That is, since the molten iron for loading raw materials is determined, the use of plates for different ships, ships, and ships makes it possible to accurately calculate transportation costs at the time when steel mills receiving raw materials are determined by optimization.

When none of the items is immobilized, or when only the "red port" is immobilized, the predicted plates for each item and both ports are used. That is, when the port and the shipment item are not determined, the port and the shipment item which are related to the vessel can be changed so that the port and the shipment item which are cheaper than the said port and the shipment item are used using the optimization mentioned later. It is possible to examine the presence or absence. In this case, by using the predicted plate for each item and for each port, it is necessary to optimize the following to change the ship's port and loading item of the ship to a port and a loading item having a lower transportation cost than the port and the loading item. By planning. This makes it possible to prepare a plan having a lower transportation cost. In addition, regarding the same molten iron | metal, the state of the record in which immobilization is not the most is considered as the molten iron | metal immobilization situation. This immobilization extraction process does not need to be the timing shown in FIG. 5, and may be performed, for example, when starting a formulation plan preparation.

(9) Optimize the formulation planning formula model based on the objective function (the planning unit 315 of FIG. 3, the formulation planning evaluation unit 359 of FIG. 4, and step S309 of FIG. 5).

The supply-demand balance model and the constellation model of the above-described linear and integer constraint equations are combined to form a formulation planning formula model, and LP (linear programming), MIP (mixed-integer programming), and QP (second-order) based on a previously constructed objective function. By calculating a problem as an optimization problem by a repair planning method such as a planning method), an optimum amount of usage and a stock amount are calculated.

Here, the example in the case of using a linear formula with respect to the objective function is shown. In this embodiment, it aims at minimizing cost (purchasing cost of a raw material, and transportation cost), and an example of the objective function J is shown to (formula 40). When obtaining using the objective function, the purchase cost information and the transportation cost information set in step S308 are used.

(40) is an example of an objective function, and may be replaced with another objective function or another objective function may be added. For example, it is necessary to approximate a compounding plan at the compounding ratio close | similar to the target compounding ratio given, and it is necessary to prepare the compounding plan which does not differ greatly between the compounding ratio of the previous day and the compounding ratio of the next day. Think of the case. In this case, an item is added to the objective function that minimizes the difference between the excess amount, the shortage amount, and the usage amount on the day and the usage amount on the day before the day from the use target amount.

By developing and setting the above formulated formula (formula model) and subtracting it with the mixed constant programming, an optimal solution for the formulation planning formula model combining the supply-demand balance model and the constellation model can be obtained.

The blending plan evaluating part 359 (plan part 315) and step S309 demonstrated above are examples of the optimization calculation part of the 2nd blending plan preparation part which it says in this invention, and the process by it.

(10) Determination of the calculation result by the optimization calculation (the calculation result determination part 360 of FIG. 4, step S310, S311 of FIG. 5)

It is determined whether or not the result obtained by the optimization calculation using (Equation 14) satisfies the mathematical model f (x _A , x _B , x _C , ..., x _N ) ≥S containing a nonlinear formula. do. As a result, if the mathematical model f (x _A , x _B , x _C ,..., X _N ) ≥S including the nonlinear equation is satisfied, then according to this result, Create calculation instructions and run the simulation. Mathematical models f (x _A , x _B , x _C ,..., X _N ) ≥S containing nonlinear equations do not satisfy ≥ S, and mathematical models f '(x _A , x _B , x _C ,..., x _N ) ≥S 'is adjusted (step S311 in FIG. 5). Specifically, the temporary lower limit S 'is slightly increased.

10 is step S307 to S310 processing, that is the formula of the non-linearity f (x _A, x _B, x _C, and and and, x _N) linear equation in place of f '(x _A, x _B, x _C, and It is a flowchart which shows the process at the time of introducing _xN ). In step S401, instead of the supply-demand balance model and the constellation model [non-linear equations f (x _A , x _B , x _C ,..., X _N ), linear equations f '(x _A , x _B , x _C , Constructed by introducing x _N ), and performing an optimization calculation based on the objective function J.

In this case, as shown in (Equation 14) ', as a lower limit for the linear expression f' (x _A , x _B , x _C , ..., x _N ), the nonlinear equation f (x _A , x _The temporary lower limit S '= S-s (s: offset value) smaller than the lower limit S for _B , x _C ,..., X _N is set.

Next, in step S402, the result obtained by optimization calculation using a mathematical model f '(x _A , x _B , x _C ,..., X _N ) ≥S' containing a linear formula is a nonlinear formula. It is determined whether or not the mathematical model f (x _A , x _B , x _C ,..., X _N )? In other words, the result (the amount of usage (mixing ratio) of each item A to N) obtained by the optimization calculation in step S401 is substituted into (Equation 14) to determine whether or not (Equation 14) is established.

As a result of Step S402, (Formula 14) is established, the process ends (step S412 of Fig. 10). On the other hand, if (Equation 14) does not hold, the routine proceeds to step S403, where the temporary lower limit S 'is slightly increased by a predetermined increase or decrease, and the process of step S401 is executed again. That is, convergence calculation which repeats the calculation by optimization calculation is performed by increasing the temporary lower limit S 'by a small amount until (Equation 14) is established.

In addition, in this embodiment, although the case where the property constraint after mixing has a lower limit was demonstrated as an example, the same also applies to the case where it has an upper limit. In this case, the linear equation f '(x _A , x _B , x _C , ..., x _N ) is the upper limit of the nonlinear equation f (x _A , x _B , x _C , ..., x _N ). I think to achieve. Further, in step S401, as the upper limit value for the linear expression f '(x _A , x _B , x _C , ..., x _N ), the nonlinear expression f (x _A , x _B , x _C , ... , x _N ) is set to a temporary upper limit value that is larger than the upper limit value.

(11) Simulate the stock trend based on the solution obtained (the stock trend simulator 311 of FIG. 3, the stock trend simulator 361 of FIG. 4, and step S312 of FIG. 5).

Based on the solution to the formulation planning formula model and all or a part of the data introduced by the input data introduction unit 351, the set plan is set for all or part of the set plan determined periods. Run the simulation with creation accuracy. In this simulation, simulations including constraints that cannot be included in the formulation planning formula model, for example, conditions that are not based on a constant rule, such as difficult to formulate, and rules of operation are simulated. This changes the solution resulting from the solution to the formulation planning formula model into a formulation plan that can be used without problems in actual operation. This makes it possible to formulate a formulation plan that takes into account the time accuracy required in actual operation and detailed constraints required for actual operation.

In addition, as an example of constraints that are difficult to handle in the mathematical model, the preparation time of preparation of equipment when the compounding ratio is changed is accurately introduced by simulating and formulating a compounding plan considering the detailed constraints required for actual operation. This becomes possible.

(12) Simulate the constellation based on the obtained solution (the constellation simulator 312 of FIG. 3, the constellation simulator 362 of FIG. 4, and step S313 of FIG. 5)

The solution to the formulation planning formula model is based on all or a portion of the inventory trend simulated by the inventory trend simulator 361 and the data introduced by the input data introduction unit 351, and then all or part of the formulation is targeted. With respect to the set planning decision period, simulation of the properties is performed with the set planning preparation precision. As a result of the simulation, results of properties after mixing of the raw materials are obtained. In this simulation, simulations including constraints, operation rules, and the like, which were not included in the formulation planning formula model are performed, thereby changing the solution resulting from the formulation planning formulation model into a formulation plan that can be used without problems in actual operation. This makes it possible to formulate a formulation plan that takes into account the time accuracy required in actual operation and detailed constraints required for actual operation.

The inventory change simulator 361 (the stock change simulator 311) and the step S312 and the constellation simulator 362 (the constellation simulator 312) and step S313 which were demonstrated above are the simulators of the 2nd compounding plan preparation part which this invention says, and Is an example of processing.

(13) Confirmation of formulation plan (determination part 363 of FIG. 4, step S314 of FIG. 5)

The plan confirmation period set from the compounding plan derived by the said inventory trend simulation and the property simulation is confirmed. As shown in FIG. 7, since the plan determination period is set to 1 day in this embodiment, the first 1-day portion of the created formulation plan is determined. About the part which was not contained in the said plan confirmation period among the created combination plans, the plan is discarded without confirmation.

(14) It is determined whether the plan for the period for planning creation or the period for the plan determination period is confirmed (the judgment unit 364 of FIG. 4, step S315 of FIG. 5).

It is judged whether the plan confirmation period determined by the execution time of this step includes the whole plan preparation period set previously. In the present embodiment, since the plan creation period is 10 days, the plan for the plan confirmation period is determined at the time when the plan is confirmed in the tenth loop. For this reason, the formulation plan for 10 days is created and a process is complete | finished at the time of finalizing a plan in 10th loop.

(15) Update of drafting start date (update part 365 of FIG. 4, step S316 of FIG. 5)

When the planning decision period determined at the time of executing this step does not include the entire planning preparation period set in advance, the date and time immediately after the formulation planning period determined in the above formulation plan is set as a new drafting start date. In this embodiment, as shown in FIG. 7, in the first loop, the drafting start date, which was originally 0 o'clock on the first day, is updated to 0 o'clock in the second day, and in the second loop, the drafting start date, which was initially 0 o'clock in the second loop, is updated to 0 o'clock on the 3rd day.

(16) Output of compounding plan [output part 366 of FIG. 4, step S317 of FIG. 5]

The mixing plan created as described above is displayed on the display unit 303 by the output unit 366 or data is transmitted to an external device including the database 400.

The output part 366 and step S317 demonstrated above are examples of the output part of the 2nd compounding plan preparation part which it says in this invention, and the process by it.

As described above, according to the current stock trend state, for the supply-demand balance constraint and the property constraint, first, a formula model is set with a plan preparation time precision for a predetermined optimization period, and the set formulation plan formula model is set as an objective function. Based on the calculated year, the inventory change and the property after mixing are simulated, and the set plan confirmation period is established among the compounding plans obtained from the simulation results, and the date and time immediately after the plan confirmation period are newly formulated. By setting it as a start date and time, a series of processes which determine the mixing | blending plan for a new planning target period are repeated one by one for a predetermined number of times. In this way, a combination plan for the desired plan preparation period can be created. Thereby, the compounding plan which requires arbitrary time accuracy can be optimized at high speed and in detail, and the obtained result can be applied to actual operation as it is.

In addition, in the said embodiment, as shown in FIG. 11, a compounding plan is created every fixed period (for example, net). In addition, a constellation model may become nonlinear with respect to several constellations (alpha), (beta). In Fig. 11, A means that the property constraint is satisfied ((Formula 14) is satisfied), and B means that the property constraint is not satisfied. That is, in the example of FIG. 11, the property violation occurred in the plural order (early and late April) with respect to the property α, and the property violation occurred in the plural order (early and late April) with respect to the property β similarly. .

In this case, if the convergence calculation described in Fig. 10 is performed separately for each order and each property, the following problem occurs. Specifically, convergence calculation is performed on constellation α in early April, convergence calculation is subsequently performed on constellation β, and convergence calculation is performed on constellation α in late April, and then convergence calculation is performed on constellation β. In doing this, the calculation process takes time.

Therefore, as described in the first embodiment, the convergence calculation described in FIG. 10 is performed by integrating the order and properties of the object. For example, convergence calculations are performed on the constellations α and β at the beginning and end of April (in step S403 of Fig. 10, a slight increase in the temporary lower limit of the constellations α and β (or a small decrease in the temporary upper limit) is performed simultaneously). ], The speed can be increased.

In addition, in the said embodiment, it demonstrated that the process of step S401 is performed again after increasing the temporary lower limit S 'by a very small amount (or reducing the temporary upper limit value by a small amount) in step S403 of FIG. In this case, the mathematical model which does not change even if the convergence calculation is changed, specifically the supply-demand balance model or the original linear constellation model, is maintained. When the temporary lower limit value is increased slightly (or the temporary upper limit value is slightly reduced), and the process of step S401 is executed again, a mathematical model that changes according to the convergence calculation, specifically, a small increase of the temporary lower limit value (or the temporary upper limit value) is performed. By making the structure change only the mathematical expression model which reduced only a small amount, speed can be achieved.

In addition, as a blending plan (for example, the amount of use (mixing ratio)), a long-term plan such as an annual plan, a preliminary plan, a monthly plan and the like is often formulated. In this way, a long-term compounding plan is prepared in advance, and the compounding plan is the standard compounding plan, and a shorter compounding plan created by the first compounding plan preparation device 100 is a certain width or more from the compounding plan that becomes the standard. It is also important to prevent it from happening.

Therefore, in addition to the objective function J constructed with respect to the cost (purchasing cost and transportation cost of the raw materials) shown in (Equation 17), the objective function J constructed with respect to the formulation plan which is a previously prepared reference and not spreading over a certain width is established. 'May be used. An example of the objective function J 'is shown in (formula 20).

In the said example, in the monthly plan, an example at the time of making a daily blending plan as a blending plan which becomes a reference | standard as a reference | standard is shown. In this case, the thing totaled every day is minimized for every item of the difference of a compounding ratio (item, day) and a reference compounding ratio. As another example, when drafting a preliminary plan, a plan may be prepared as a compounding plan based on the annual plan. In this case, when the monthly rate determines that the compounding ratio (item, month) is determined, the monthly sum of the difference between the compounding ratio (item and month) and the standard compounding ratio is minimized for each item.

In addition, the formulation plan used as a reference | standard is created based on the past performance, for example, and the preparation method may be anything. Of course, a long-term plan may be prepared in advance by the blending plan preparation method to which the present invention is applied, and it may be used as a blending plan as a reference.

As described above, it becomes possible to collectively create a blending plan for receiving and mixing a blended raw material of a plurality of items and a wiring plan for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites. In addition, in these plans, it becomes possible to minimize transportation cost as a whole through a compounding plan and a wiring plan. Moreover, the compounding plan / wiring plan which can prevent stock shortage more reliably than when using a 1st compounding plan preparation device 100 creates a use plan, and creates a wiring plan using this use plan as input data. You can write

(Third embodiment)

In the said 2nd Embodiment, in the wiring plan preparation apparatus 200, as a restriction | limiting (formula 24) regarding the stock of each item, the safety stock amount may not fall for every individual item. In actual operation, however, items having close properties (plural items having common chemical properties included in the prescribed range: items which can be used even if they are substituted with each other) are used by being substituted with each other, which is flexible. For example, if the inventories of raw materials A and B are 50,000 tons and 0 tons, respectively, if the raw material A is 0 tons and B is 20,000 tons in the plan of use, inventory shortage may occur considering only B items. However, when the properties of the raw materials A and B are interchangeable with each other, the operation of using 20,000 tons of A instead of 20,000 tons of the raw materials B is performed. By doing in this way, a stock shortage can be prevented.

For example, in the case of coal, "The degree of carbonization is 70% or less; Greater than 70% and not more than 90%; Greater than 90% ”and the like are grouped using the conditions relating to the physical or chemical properties of the raw materials. In addition, by grouping items in this way and treating them as one, it is possible to reduce the amount of calculation by reducing the number of variables.

In this embodiment, it aims at realizing preparation of the mixing | blending plan and wiring plan which implement | achieve the said operation. For this reason, in the wiring plan preparation apparatus 200, the restriction | limiting regarding the stock of each item is not handled by not dropping the safety stock amount for every individual item, but the items which have the property which can replace each other are grouped and handled. do. In other words, in the grouped items, inventory constraints are created on the assumption that the inventory amount of the items as a group does not lower the safety inventory amount as a group.

That is, in the wiring plan preparation device 200, instead of (Expression 24), a constraint equation indicating that the stock amount of each grouped item is always secured or more as a safety stock as a group is used. This constraint is represented by the following formula (42).

By grouping and handling items in this way, it is possible to transport items that can be arranged from the same item to cheaper ships, instead of the items that can only be transported by ships with a higher plate rate, thereby reducing transportation costs. have. For example, consider the case where there are raw materials X and Y having almost the same properties, and in both ports (steelworks) A, use by the raw materials X and Y is also possible. The cost of transporting raw material X to port A is 20 $ / ton, the cost of transporting raw material Y is 40 $ / ton, the cost of transporting raw material X to port B is 40 $ / ton, and the cost of transporting raw material Y 20 $ / The amount of tons and the initial stock is all zero, and for some reason, such as the relationship with other steel mills, 0 tons of raw material X is used at port A, 50,000 tons of Y is used, and 50,000 tons of raw material X is used at port B. Consider the case where a formulation plan in which 0 Y is used is created by the first formulation plan preparation device 100. In this case, in the case where the inventory of the items is individually maintained in the wiring plan, the wiring in which 50,000 tons of the raw material Y is loaded in both ports A and 50,000 tons of the raw material X in both ports B is derived from the stock constraint. In this case, a transportation cost of 40 $ / tonne x 50,000 tons X 2 is required. However, if a group of items having a replaceable property is considered as a group, both ports A and B may have a wiring plan, in which case a plan for loading 50,000 tons of raw material X into 50,000 A and 50,000 tons of raw material Y into both ports B is made as a wiring plan. The stock amount of the sum of X and Y does not fall below 0, and the stock constraint is satisfied. The transportation cost in this case is 20 $ / ton * 50,000 tons × 2, which is half the cost compared with the case where no group is considered.

As described above, it becomes possible to collectively create a blending plan for receiving and mixing a blended raw material of a plurality of items and a wiring plan for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites. In addition, in these plans, it becomes possible to minimize transportation cost as a whole through a compounding plan and a wiring plan. In addition, by using the first formulation planning preparation device 100, a usage plan is created, and as an input data relating to this usage plan, a wiring plan that does not drop inventory is considered by considering items having replaceable properties as a group. In comparison with the case, it is possible to create a compounding plan and a wiring plan that are more inexpensive to transport.

(4th embodiment)

In 3rd Embodiment, the use plan is created by the 1st compounding plan creation apparatus 100, and this item is used as input data, and the item which has a replaceable property is considered as a group, and does not drop inventory. An embodiment for creating a wiring plan has been described.

However, in actual operation, it is often necessary to secure stock for each individual item as a final compounding plan and wiring plan. That is, in the said 3rd Embodiment, when changing between groups, the item which can be replaced by the use plan created by the 1st compounding plan creation apparatus 100 and the wiring plan created by the wiring plan preparation apparatus There is no shortage of inventory as a group. However, as individual items, variations occur between the use and the stocking of the items, so that when the stock is viewed as individual items, the stock appears to be out of stock, causing a problem that an operator is difficult to handle. As an embodiment for solving this problem, the formulation according to the arrival is made by creating a formulation plan by the second formulation plan preparation device 300 using the wiring plan created by the wiring plan preparation device 200 as input data. It is possible to make a plan. In this case, since the replacement | exchange is performed between the items which have a replaceable property, also in the 2nd compounding plan preparation apparatus 300, it becomes possible to create a compounding plan without unreasonableness to a property constraint. In addition, in the 1st compounding plan preparation apparatus 100, since the use plan is created based on the acquisition target amount in the state in which the ship is not determined, precision is not good as a use plan. However, since the use plan is created in the state in which the vessel is determined by the wiring plan preparation device, that is, in the state determined by the arrival, the second compounding plan preparation device 300 can create a more accurate use plan.

According to the above structure or method, it becomes possible to collectively create a blending plan for receiving and mixing a plurality of blended raw materials and a wiring plan for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites. In addition, in these plans, it becomes possible to minimize transportation cost as a whole through a compounding plan and a wiring plan. Moreover, compared with the case where a usage plan is created by the 1st compounding plan creation apparatus 100, and a wiring plan is created using this use plan as input data, it is possible to create a compounding plan and a wiring plan having a lower transportation cost. It becomes possible. In addition, it is possible to create a high-precision usage plan by creating a usage plan by the second compounding plan preparation device 300.

27 shows an example of a hardware configuration of a computer device 2500 that can function as the compound planning device 100, 300 or the wiring plan preparation device 200 of the present invention. CPU 2501, which is a central processing unit for controlling the entire apparatus, a display portion 2502 for displaying various input conditions and results, a storage portion 2503 such as a hard disk for storing results, etc., a control program, various application programs, ROM (read only memory) 2504 for storing data and the like, RAM (random access memory) 2505 which is a work area used by the CPU 2501 to perform processing, and input units 2506 such as a keyboard and a mouse. It is composed.

Further, program codes of software for realizing the functions of the above embodiments are supplied to a computer in the apparatus or system connected with the various devices so as to operate the various devices in order to realize the functions of the above embodiments, What was implemented by operating the said various device according to the program stored in the computer (CPU or MPU) of the system or apparatus is also included in the scope of the present invention. In this case, the program code itself of the software realizes the functions of the above-described embodiments, and means for supplying the program code itself and the program code to a computer, for example, a recording medium storing such a program code is Configure the invention. As a recording medium for storing program codes, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

The present invention further includes the following aspects.

(1) When the mixed raw materials of a plurality of items transported by a ship from a plurality of sources to a plurality of sources and received are mixed and used at each supply source, the mixing plan of the mixed raw materials of the plurality of items and the blended raw materials of the plurality of items are used. Is a compounding and wiring planning system for creating a wiring plan for a vessel transported from a plurality of supply sources, which is a shipping place, to a plurality of supply sites, which are based on a predetermined acquisition target amount of the blended raw materials, for each supply source, and for each item. Based on the first blending plan creation means for preparing a blending plan for receiving and mixing blended raw materials and the blending plan created by the first blending plan creating means, a plurality of items of blended raw materials are transferred from the plurality of shipping destinations to the plurality of landing sites. Wiring plan preparation means to make wiring plan to transport and the wiring plan work Formulation and wiring plan creation system which is characterized in that it includes a database means for storing a wiring plan created by the means.

(2) The said 1st formulation planning preparation means introduces data containing the acquisition target amount of a blended raw material, the stock situation of a blended raw material, the property of a blended raw material, the purchase cost information of a blended raw material, and the transport cost information when using a ship. And a data model for introducing data, a simulator for calculating the supply and demand state of the blended raw materials, and a formula model for constructing a formula model representing the supply and demand balance constraints of the blended raw materials and a property constraint after mixing; Optimization calculation means for performing optimization calculation on the basis of the objective function constructed with respect to the purchase cost and transportation cost of the blended raw materials by using the formula model constructed by the formula model construction means, and calculating instructions for the simulator; Output means for outputting the formulation plan which is the simulation result by the simulator The compounding and wiring plan preparation system as described in said (1) characterized by the above-mentioned.

(3) In the optimization calculation means of the first formulation planning preparation means, the optimization calculation is further performed based on the objective function constructed with respect to the relationship between the amount of the incoming raw material and the acquisition target amount. Formulation and wiring planning system.

(4) The transportation cost information introduced by the data introduction means of the first mixing plan preparation means includes information of a plate for each ship, a port, and a port, and information for a plate for each item and a port. The compounding and wiring plan preparation system as described in said (2) or (3).

(5) The said 1st formulation plan preparation means calculates the estimated use amount of the compounding raw material by the created formulation plan, and the said wiring plan preparation means is a mixture raw material by the formulation plan created by the said 1st formulation plan preparation means. List of vessels listed in the list of vessels with different usage schedule, acquisition target quantity, contract type, operation status of vessels listed in the vessel list, inventory status of blended raw materials, purchase cost information of blended raw materials, and the ship list. Data introduction means for introducing data including transportation cost information when using a listed ship, inventory trend simulator for calculating inventory trend of blended raw materials, and ship operation status trend simulator for calculating trend of ship operation status A simulator configured by the ship and the ship based on the ship navigation situation. A ship finance means for selecting a vessel from the night list and creating the necessary ship resources, and at least the ship's operational constraints, the supply and demand balance of the blended raw materials at the landing site, and the acquisition target quantity constraints. Using mathematical formula building means for constructing a mathematical model and mathematical formula model constructed by the mathematical model constructing means, optimization calculation is performed based at least on an objective function constructed with respect to transportation costs, and an instruction to the simulator is calculated. The compounding and wiring plan preparation system in any one of said (1)-(4) provided with the optimization calculation means to perform, and the output means which outputs the wiring plan which is a simulation result by the said simulator.

(6) Said wiring plan preparation means is a ship list by which the ship which differs in the use scheduled amount of the raw material mix, the acquisition target amount, and the type of contract by the formulation plan created by the said 1st formulation plan preparation means is listed up, and the said vessel list. It includes the operation status of the listed ships, the inventory status of the compounded raw materials handled by grouping items close to the above properties, the purchase cost information of the compounded raw materials, and the transport cost information when using the ships listed in the ship list. A simulator configured by a data introduction means for introducing data, a stock trend simulator for calculating inventory trends of blended raw materials handled by grouping items having similar properties, and a ship flight status trend simulator for calculating trends of ship navigation conditions. And the ship list based on the ship navigation situation. Supply and demand of the raw material of the ship which prepares the ship resource from the ship selection means which selects a ship from a ship, and prepares the required ship resources, and the group which handles at least the said operation condition of the ship created by the said ship finance means, and the item near the property at the landing place. Optimization calculations are performed based on at least the objective function constructed with respect to transportation costs, using mathematical model construction means for constructing a mathematical model representing balance constraints and argument target quantity constraints, and the mathematical model constructed by said mathematical model construction means; And a combination calculation device according to any one of (1) to (4), comprising: an optimization calculation means for calculating an instruction to the simulator; and an output means for outputting a wiring plan that is a simulation result by the simulator. Wiring plan creation system.

(7) Based on the wiring plan created by the said wiring plan preparation means, 2nd formulation planning preparation means which prepares the formulation plan which receives and mixes several compounding raw materials, and was created by the said 2nd formulation plan preparation means. The compounding and wiring plan preparation system in any one of said (1)-(6) characterized by including the database means which stores a compounding plan.

(8) The said 2nd compounding plan preparation means is for carrying out the arrival schedule of the compounding raw material by the wiring plan created by the said wiring plan preparation means, the stock situation of the compounding raw material, the property of the compounding raw material, the purchase cost information of the compounding raw material, and the ship. A data introduction means for introducing data including transport cost information at the time of use, a simulator for calculating the supply and demand condition of the blended raw materials, a mathematical model representing the supply and demand balance constraints of the blended raw materials, and a property constraint after mixing Using the mathematical model construction means for constructing the mathematical model and the mathematical model constructed by the mathematical model construction means, optimization calculation is performed based on the objective function constructed with respect to the purchase cost and transportation cost of the blended raw material, and the simulator Optimization calculation means for calculating an instruction to Formulation and wiring plan creation system according to the above (7), characterized in that it includes output means for outputting a simulation result of the combined scheme.

(9) The compounding and wiring plan preparation system according to any one of (1) to (8), wherein the compounding plan created by the first compounding plan preparation unit is handled by grouping items with close properties.

(10) When the mixed raw materials of a plurality of items transported and received by a ship from a plurality of sources to a plurality of sources are mixed and used at each supply source, a mixing plan of the mixed raw materials of the plurality of items and a blending raw material of the plurality of items Is a formulation and wiring plan preparation method for creating a wiring plan for a vessel to be transported from a plurality of supply sources, which is a shipping place, to a plurality of supply destinations, wherein a first formulation planning means is set in advance for each supply source and item of the blended raw materials. Based on the acquisition target quantity, the step which prepares the mixing | blending plan which receives and mixes the compounding raw material of several items, and wiring plan preparation means are raw materials of several items based on the mixing | blending plan created by said 1st mixing plan preparation means. Creating a wiring plan for transporting air from a plurality of shipping destinations to a plurality of landing sites, and the ship Formulation and wiring plan creation method for a wiring plan created by the program creation unit is characterized by having the step of storing in the database means.

(11) A program for operating a computer as each means of the compounding and wiring plan preparation system according to any one of (1) to (9).

According to the present invention, a blending plan for receiving and mixing a plurality of blended raw materials and a wiring plan for transporting a plurality of raw materials from a plurality of shipping destinations to a plurality of landing sites can be collectively prepared. In particular, in consideration of ships with different types of charter party contracts, an objective function constructed with respect to transportation costs can be prepared, and an optimization calculation can be performed based on this objective function. This makes it possible to plan for minimizing transportation costs, including whether to use the type of the charter party (continuous sailing ship, irregular liner, spot ship), or whether to use the ship to determine the configuration of the ship. In addition, even in the compounding planning step, it is possible to prepare a plan in consideration of minimizing the transportation cost.

100: first formulation plan preparation device
200: wiring plan preparation device
201: simulator
202: macro optimizer
202a: Ship finance list preparation unit
202b: Equation model setting unit
202c: optimization calculation unit
203: micro optimizer
203a: formula model setting unit
203b: optimization calculation unit
204 data introduction
205: output unit
300: second formulation plan preparation device
303: display unit
304: operator evaluation unit
312: constellation simulator
313: supply and demand balance model setting unit
314: constellation model setting unit
315: Planning Department
351: input data introduction unit
352: planning period setting unit
353: time precision setting unit
354: optimization period setting unit
355: Planning fixed period setting unit
356: supply and demand balance model setting unit
357: constellation model setting unit
357a: linearization unit
358: immobilized extraction processing unit
359: compounding planning
360: confirmation unit
361: Stock Trend Simulator
362: Constellation Simulator
363: Confirmation
364: judgment unit
365: renewal unit
366: output unit
400: database
500: computer

Claims (14)

A wiring plan for transporting blended raw materials of a plurality of items from a plurality of shipping destinations to a plurality of landing sites,
It is a compounding and wiring plan making system which prepares the compounding plan which mixes the said compounding raw materials received in each said landing place,
A first blending plan preparation unit for preparing a first blending plan based on a target acquisition amount of the blended raw materials set in advance for each of the shipping destinations and the items;
A wiring plan preparation unit for creating the wiring plan based on the created first formulation plan;
And a database unit for storing the created wiring plan. The formulation and wiring plan preparation according to claim 1, wherein in the preparation of the formulation plan and the preparation of the wiring plan, common constraints are used with respect to the acceptance target amount and the stock situation of the compounding raw material. system. The said 1st compounding plan preparation part of Claim 1,
A data introduction unit for introducing data including the acquisition target amount of the blended raw material, the stock situation of the blended raw material, the properties of the blended raw material, the purchase cost of the blended raw material, and the transport cost of the blended raw material;
A mathematical model setting unit which sets formula models representing supply and demand balance constraints of the blended raw materials and property constraints after mixing of the blended raw materials;
An optimization calculation unit which performs optimization calculation based on the objective function pre-built with respect to the purchase cost and the transportation cost, using the set formula model;
A simulator which operates based on the results of the optimization calculations and simulates the transition of supply and demand of the blended raw materials and the trend of the properties after mixing of the blended raw materials;
And an output unit for outputting a compounding plan which is a simulation result by the simulator. The formulation and wiring plan preparation system according to claim 3, wherein the optimization calculation unit performs optimization calculation further based on an objective function built in advance regarding the relationship between the amount of the blended raw material and the acquisition target amount. The transportation cost according to claim 3 or 4, wherein the transportation cost introduced by the data introduction unit includes:
Information of plates by ship, port and port,
The formulation and wiring plan preparation system, characterized by including the information of the plate according to the item and the port. The said 1st formulation planning preparation part is further, The estimated use amount of the said compounding raw material according to the said formulation plan created,
The wiring plan preparation unit,
A list of ships listing a plurality of vessels operated on the basis of the scheduled use amount of the blended raw material, the target acquisition amount of the blended raw material, the stock situation of the blended raw material, the purchase cost of the blended raw material, and a plurality of types of charter party contracts. A data introduction unit for introducing data including a flight status and a transportation cost of each of the vessels;
A vessel finance list preparation unit for selecting the vessel as a candidate for wiring from the vessel list on the basis of the navigation situation and creating a vessel finance list;
A mathematical model setting unit for setting a mathematical model representing the operational constraints of the vessel included in the vessel resource list, supply and demand balance constraints of the blended raw materials at the landing place, and limitations on target acquisition amounts;
An optimization calculation unit for performing optimization calculations based on the objective function built in advance with respect to the transportation cost by using the set equation model;
A simulator which includes a stock trend simulator for simulating the trend of the stock situation, a ship operational status trend simulator for simulating the trend of the flight status, and which operates based on a result of the optimization calculation;
And an output unit for outputting the wiring plan which is a simulation result by the simulator. The said 1st formulation planning preparation part is further, The estimated use amount of the said compounding raw material according to the said formulation plan created,
The wiring plan preparation unit,
The stock situation of the grouped blended raw materials in which the blended raw materials of a plurality of the items included in the prescribed ranges of the blended raw materials, the target acquisition amount of the blended raw materials, and properties are grouped and handled, and the cost of purchasing the blended raw materials A data introduction unit for introducing data including a list of ships listing a plurality of ships operated on the basis of a plurality of charter charter agreements, operational conditions and transportation costs of each of the ships;
A vessel finance list preparation unit for selecting the vessel as a candidate for wiring from the vessel list on the basis of the navigation situation and creating a vessel finance list;
A mathematical model representing the supply and demand balance of the grouped blended raw materials handled by grouping the blended raw materials of the plurality of the items included in the prescribed ranges of the ship's operating resources and properties included in the ship's resource list, and the target amount of constraints. An equation model setting unit for setting
An optimization calculation unit for performing optimization calculations based on the objective function built in advance with respect to the transportation cost by using the set equation model;
A stock trend simulator for simulating the trend of the stock situation of the grouped blended raw materials in which the blended raw materials of a plurality of the items whose properties are included in a prescribed range are grouped and handled, and a ship sailing situation for simulating the trend of the operational status A simulator including a transition simulator and operating based on a result of the optimization calculation;
And an output unit for outputting the wiring plan which is a simulation result by the simulator. The second formulation plan preparation unit according to any one of claims 1, 3, and 7, further comprising a second formulation plan creation unit based on the created wiring plan.
And the database unit further stores the second formulation plan. The said 2nd compounding plan preparation part of Claim 8,
Second data which introduces data including the arrival schedule of the said compounding raw material based on the said wiring plan, the stock situation of the said compounding raw material, the property of the said compounding raw material, the purchase cost of the said compounding raw material, and the transport cost of the said compounding raw material. Introduction,
A second mathematical model setting unit which sets formula models representing the supply and demand balance constraints of the blended raw materials and property constraints after mixing of the blended raw materials, using the arrival schedule;
A second optimization calculator which performs optimization calculation based on the objective function built in advance with respect to the purchase cost and the transport cost by using the set formula model;
A second simulator operating on the basis of the results of the optimization calculations and simulating the transition of supply and demand of the blended raw materials and the transition of the properties after mixing of the blended raw materials;
And a second output unit for outputting a compounding plan which is a simulation result by the simulator. 10. The method according to claim 9, wherein in the supply and demand balance constraints of the first formulation plan and the supply and demand balance constraints of the second formulation plan, the same constraints are set with respect to demand,
In the supply-demand balance constraint of the first formulation plan, the supply target amount is set as a constraint with respect to the supply,
In the supply-demand balance constraint of the second compounding plan, the amount of raw materials received by the ship is set as a constraint with respect to the supply, wherein the compounding and wiring plan preparation system. The said objective function of the said 1st formulation plan WHEREIN: The estimated plate by item and both ports are used,
In the said objective function of a said 2nd compounding plan, the plate | board, ship, and port-specific board | plate specific plate is used, The formulation and wiring plan preparation system characterized by the above-mentioned. The compounding and wiring plan preparation system according to claim 1 or 3, wherein in the prepared compounding plan, the compounding raw materials of a plurality of the items included in a range whose properties are defined are grouped and handled. A wiring plan for transporting blended raw materials of a plurality of items from a plurality of shipping destinations to a plurality of landing sites,
It is a compounding and wiring plan making method which prepares the compounding plan which mixes the said compounding raw materials received in each said landing place,
A first compounding plan preparation step of preparing a first compounding plan based on the acceptance target amounts of the compounding raw materials set in advance for each of the shipping places and for each item;
A wiring plan preparation step of creating the wiring plan based on the created first formulation plan;
And a database storage step of storing the created wiring plan in a database. A program for operating a computer as each part of the compounding and wiring plan preparation system according to claim 1.

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