JP2009277095A - Production plan making device, production plan making method, program, and computer-readable storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To make a production plan satisfying constraint on a facility and the date of delivery or the like and working products with the same attributes in a batch in the maximum lot, in a manufacturing plant which produces a plurality of types of products. <P>SOLUTION: This production plan making device is configured to make a production plan by an order information storage database 101 for storing a plurality of order information; an order information input part 102 for receiving a plurality of order information from the database 101; a constraint formula setting part 103 for setting a constraint formula represented with variables x representing the constraint of the facility and the date of delivery on the basis of order information; an evaluation function setting part 104 for setting evaluation functions represented with variables δ as a subset of the variables x; an optimal solution calculation part 105 for calculating the value of the optimal variable x satisfying the constraint formula by maximizing or minimizing the value of the evaluation function under such conditions that the value of the variable δ is an integer of 0 or 1; and an output/display part 106 for outputting and displaying a production plan configured of operation conditions corresponding to the value of the variable x calculated by the optimal solution calculation part 105. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a production plan planning apparatus, a production plan planning method, a program, and a computer-readable storage medium for automatically collecting a plurality of lots and planning a production plan based on attributes of a plurality of orders given in the manufacturing industry. In particular, the present invention relates to a technique suitable for use in drafting a steel production plan in the metal product manufacturing industry.

  When planning a production plan for a factory in the manufacturing industry, it is often the case that a plurality of orders are collected into lots of an appropriate size from the viewpoint of improving productivity by mass production when manufacturing a plurality of orders.

  For example, in the steel manufacturing industry, it is required to produce lots of orders with the same chemical composition of products in steelmaking facilities in batch units, and steelmaking facilities basically aimed at mass production of steel of the same components. Equipment. In a large-scale steelworks, a molten steel pan of about 300 to 350 tons is refined as one charge, and 7 to 15 charges are cast as one cast and continuously cast in a continuous casting facility (so-called continuous casting). In the continuous casting process, the same cast has more charges of the same component (the larger the lot), the smaller the number of joints (charges of different steel types) between charges of different components, and the yield is improved. preferable.

  On the other hand, the manufacturing process consists of multiple manufacturing facilities such as steelmaking, rolling, refining, shipping, etc. Pursuing lot productivity in the steelmaking process reduces the productivity of other manufacturing facilities, Lot summarization may lead to concentration of manufacturing load in the downstream process, which may cause an increase in work in progress and an increase in the manufacturing period. In addition, pre-fabrication for making a lot may cause extra product inventory and a corresponding increase in work period. That is, it is necessary to create a production plan that can produce as much steel as possible in the steelmaking facility while satisfying the facility constraints and the delivery date constraints.

  In order to solve such a problem, Patent Document 1 discloses that the provisional steel desired date is calculated backward by the standard work period between each process on the basis of the production recording management date, and the steel type is classified into the steel type in order of the provisional steel desired date. A method is disclosed that achieves equalization of the operating rate and delivery date management of each production line by creating lots and then putting them into production processes according to a predetermined priority.

  Further, in Patent Document 2, in order to achieve leveling of the manufacturing load in the lower process, each type classified based on the manufacturing process is assigned to the capacity frame of the lower process, and a casting request date is given. A method of allocating to a rough production lot by a quadratic programming method is disclosed so that the difference between the charge equivalent and the requested casting amount is minimized for each type of requested day.

JP 05-35748 A JP 2005-259122 A

  However, the invention described in Patent Document 1 is that production lots are created for each type of steel in the order of the desired provisional steel date, and then are put into the production process according to a predetermined priority order. There was a problem that the optimality of compliance and lot size was not guaranteed.

  Further, the invention described in Patent Document 2 applies a plurality of types to a rough production lot that is a steel output frame of a plurality of steel types, and does not disclose how to obtain the rough production lot.

  The present invention has been made in view of the situation as described above, and based on the attributes of multiple orders for multiple types of products given in the manufacturing industry, while satisfying various constraints such as equipment and delivery time, The purpose is to automatically assemble orders into a plurality of lots so that the size of the lot is optimal and to make a production plan.

The production plan planning device of the present invention is a production plan planning device for planning a production plan for processing a product having the same attribute in a lot in a manufacturing plant that produces a plurality of types of products,
A database that stores multiple order information;
Input means for fetching the plurality of order information from the database;
Based on the order information fetched by the input means, a constraint expression setting means for setting a constraint expression using the variable x representing equipment and delivery date constraints;
Evaluation function setting means for setting an evaluation function expressed using a variable δ which is a subset of the variable x;
An optimal solution for calculating the value of the variable x that is optimal by maximizing or minimizing the value of the evaluation function under the condition that the constraint equation is satisfied and the value of the variable δ is an integer of 0 or 1 A calculation means;
Output display means for outputting and displaying a production plan composed of operating conditions corresponding to the value of the variable x calculated by the optimum solution calculating means.
Further, another feature of the production planning apparatus according to the present invention is that the evaluation function is a sum of the variables δ of 0 or 1 representing whether or not manufacturing is performed by manufacturing date or manufacturing time and by type. It is in.
Another feature of the production planning apparatus according to the present invention is that the optimum solution calculating means partially relaxes the condition that the variable δ is an integer of 0 or 1, and A process of calculating a real value of the variable x that satisfies the constraint equation and optimizes the value of the evaluation function as a maximum or minimum under a condition that a value of a part is a non-integer, and the variable δ The process of fixing a part or all of the variables δ having 0 values to 0 among the variables δ belonging to the manufacturing time provided with integer conditions is repeated until all the variables δ become integer values. is there.
Another feature of the production planning apparatus of the present invention is that the optimum solution calculating means satisfies the constraint equation using a mixed integer programming method, and maximizes or minimizes the value of the evaluation function value. It is in the point to be optimal.
The production plan planning apparatus method of the present invention is a production plan planning method for planning a production plan for processing a product having the same attribute in a lot in a manufacturing plant that produces a plurality of types of products,
An order information storage step for storing a plurality of order information in a database;
Order information input step for fetching the plurality of order information from the database;
A constraint equation setting step for setting a constraint equation using the variable x representing the facility and delivery date constraint based on the order information captured in the input step;
An evaluation function setting step for setting an evaluation function expressed using a variable δ that is a subset of the variable x;
An optimal solution for calculating the value of the variable x that is optimal by maximizing or minimizing the value of the evaluation function under the condition that the constraint equation is satisfied and the value of the variable δ is an integer of 0 or 1 A calculation step;
An output display step for outputting and displaying a production plan composed of operation conditions corresponding to the value of the variable x calculated in the optimum solution calculating step.
Further, another feature of the production planning method of the present invention is that the evaluation function is a sum of the variables δ of 0 or 1 representing whether or not manufacturing is performed by manufacturing date or manufacturing time and by type. It is in.
Another feature of the production planning method of the present invention is that, in the optimum solution calculating step, the condition that the variable δ is an integer of 0 or 1 is partially relaxed, and A process of calculating a real value of the variable x that satisfies the constraint formula and optimizes the evaluation function value as a maximum or a minimum under a condition that a part is a non-integer, and an integer for the variable δ Among the variables δ belonging to the manufacturing time for which conditions are set, the process of fixing a part or all of the variables δ having 0 values to 0 is repeated until all the variables δ become integer values.
Another feature of the production planning apparatus according to the present invention is that, in the optimum solution calculating step, the constraint equation is satisfied using a mixed integer programming, and the value of the evaluation function value is maximized or minimized. It is in the point to be optimal.
The program of the present invention is a program for creating a production plan for processing products having the same attribute in a lot in a manufacturing plant that produces a plurality of types of products,
Order information storage processing for storing a plurality of order information in a database;
Order information input processing for fetching the plurality of order information from the database;
Based on the order information captured in the order information input process, a constraint expression setting process for setting a constraint expression using a variable x representing a facility and a delivery date constraint;
An evaluation function setting process for setting an evaluation function represented using a variable δ which is a subset of the variable x;
An optimal solution for calculating the value of the variable x that is optimal by maximizing or minimizing the value of the evaluation function under the condition that the constraint equation is satisfied and the value of the variable δ is an integer of 0 or 1 Calculation process,
And causing the computer to execute an output display process for outputting and displaying a production plan including an operation condition corresponding to the value of the variable x calculated by the optimum solution calculating means.
A computer-readable storage medium according to the present invention records the program according to the present invention.
In the present invention, the type (product type) refers to a product having different manufacturing specifications. The attribute (product attribute) is a key that can be collected in the same lot.

According to the present invention, in a manufacturing plant that produces a plurality of types of products, when a production plan is obtained in a manufacturing process in which products having the same attribute are processed together in a lot under a certain constraint condition, all facilities to be considered A lot plan can be created by setting a delivery date constraint and optimizing the value of the evaluation function for judging the quality of the lot plan.
In particular, the variable δ of 0 or 1 representing the presence / absence of production by production date or production time and type is not optimized for calculation under the condition that it is an integer, but only the variable δ belonging to the latest production time is set to an integer condition. Set and calculate the optimal solution, among the variables δ belonging to the manufacturing time with the integer condition for the variable δ, fix some or all of the variables δ having 0 value to 0, and set the integer condition to the variable δ It is possible to create an optimized lot plan at a high speed even when the number of orders is large or the planning period is long by repeating the process of expanding the section and calculating the optimum solution until all the variables δ become integer values.

Preferred embodiments of the present invention will be described below with reference to the accompanying drawings.
FIG. 1 shows a schematic configuration of a production plan planning apparatus according to an embodiment to which the present invention is applied. The production plan planning apparatus according to the present embodiment plans a production plan in which products having the same attribute are collectively processed into lots in a manufacturing plant that produces a plurality of types of products, and includes an order information storage database 101 and input means. An order information input unit 102 that functions as a constraint equation setting unit 103 that functions as a constraint equation setting unit, an evaluation function setting unit 104 that functions as an evaluation function setting unit, an optimal solution calculation unit 105 that functions as an optimal solution calculation unit, and an output An output / display unit 106 that functions as display means is provided. These functions are described in detail below.

  FIG. 2 shows a flowchart of a production plan planning method by the production plan planning apparatus according to the present embodiment. First, the order information input unit 102 fetches order information from the order information storage database 101 in which order information is stored (order information input step (process) S201).

  Next, the constraint equation setting unit 103 creates and sets a constraint equation using the variable x representing the facility and the delivery date constraint based on the order information fetched by the order information input unit 102 (constraint equation setting step (processing)) S202).

  Next, the evaluation function setting unit 104 sets an evaluation function expressed using a variable δ, which is a subset of the variable x, in order to determine the quality of the lot plan (evaluation function setting step (process) S203). .

  Next, the optimal solution calculation unit 105 satisfies the constraint equation and sets the value of the variable x to be the optimum value by minimizing the value of the evaluation function under the condition that the value of the variable δ is an integer of 0 or 1. (Optimal solution calculation step (process) S204). Here, an example is given in which the value of the evaluation function is minimized and optimized, but the value of the evaluation function may be maximized and optimized.

  Then, the output / display unit 106 outputs and displays a production plan composed of operation conditions corresponding to the value of the variable x calculated by the optimal solution calculation unit 105 (output / display step (process) S205).

  Hereinafter, each means (step, process) will be described in detail. The order information storage database 101 stores attributes, manufacturing specifications, and the like as a plurality of order information. For example, as shown in Table 1, for 12 types of products, the chemical composition of steel types A, B, and C as attributes, and the probability of passing through the gas process, the straightening process, and the care process as manufacturing specifications (process occurrence rate), respectively. It is specified and is divided into 14 stages of 0 to 13 (days) in the order of the steel output timing as the order input amount (unit: ton) according to the steel output date.

  As shown in FIG. 2, in the order information input step (S201), the order information shown in Table 1 is stored in an external storage device such as a hard disk drive or a semiconductor memory reader / writer connected to the computer, a keyboard, or the like. From an external input device such as a touch panel, or from an information processing device or the like that is an external device installed in a manufacturing factory or the like, it is input to the computer via a network and is read into the memory of the computer. The network may be, for example, the Internet, an optical fiber network, a sanitary communication network, a telephone line network, Ethernet (registered trademark), a LAN, a dedicated cable, or other various dedicated line networks or public line networks.

  In the constraint formula setting step (S202), based on the above order information, the constraint formula for the facilities and the delivery date is set using the variable x representing the facilities used for making the production plan and the delivery date constraint. Specifically, the variable x is the parameters necessary for creating the steel production plan amount by production time, the constraints of equipment and delivery time constraints (production by process, delivery delay amount, production by production time attribute) 0 or 1 variable δ representing the presence or absence).

Next, in the evaluation function setting step (S203), in order to determine the quality of the lot plan, an evaluation function expressed using a variable δ which is a subset of the variable x is set and stored in the memory. The evaluation function is represented by the sum of 0 or 1 variable δ _{ik indicating} the presence or absence of steel production of the k-day i steel type. Instead of the manufacturing date (kth day), the manufacturing time (kth with respect to the reference time) may be used. When the amount of steel output of the k-day i steel type is C _ik , the variable δ _ik and the amount of steel output C _ik are expressed by the relationship of the following equation (1). The variable δ _ik and the steel output C _ik are a subset of the variable x, and the maximum value of the steel output C _ik is M.

Using the variable _δik , the evaluation function is set as in the following equation (2).

Next, in the optimum solution calculation step (S204), a variable x that satisfies the equipment and delivery date constraints and minimizes the evaluation function value J obtained by the evaluation function of Expression (2) is obtained. FIG. 3 shows a processing flow of the optimum solution calculating step (S204). First, in the initialization step (S301), the fixed variable area used in the subsequent calculations is empty, the repetition counter n = 0, and the initial integer condition interval m is set to 3, for example. The fixed variable is a memory area for storing a variable _δik that is fixed to 0 at the time of optimization calculation. The integer condition interval is a period during which the variable δ _ik is not relaxed to a non-integer.

In the relaxation problem creation step (S302), a relaxation problem is created in which the variable δ _ik (1 ≦ k ≦ m) is relaxed to an integer condition and the variable δ _ik (m <k) is relaxed to a non-integer condition.

  In the relaxation optimal solution calculation step (S303), the optimal solution of the relaxation problem created in the relaxation problem creation step (S302) is calculated by the mixed integer programming method, and this is set as relaxation optimization.

In the integer determination step (S304), if all the variables _δik are integers, the relaxed solution optimal solution is output as the optimal solution. Otherwise, in the constraint condition changing step (S305), the integer condition interval m and the iteration counter n are incremented by 1, and only the variable δ _ik (m ≦ k) of the relaxed optimal solution that is 0 is fixed to 0. Then, the process proceeds to the relaxation problem creating step (S302), and thereafter this step is repeated until all the variables _δik become integer values.

That is, the condition that the variable δ _ik is an integer of 0 or 1 is partially relaxed, the constraint equation is satisfied under the condition that a part of the value of the variable δ _ik is a non-integer, and the evaluation function a process of calculating the real value of the variable x to optimize by a value to a minimum, the variable [delta] of the variable [delta] _ik belonging to manufacturing time provided an integer conditions _ik, some or all of the variable [delta] _ik having 0 value Is repeated until the variables δ _ik all become integer values. In this way, the integer variable is relaxed to a non-integer, and the integer condition interval is gradually expanded to solve the optimization problem, thereby suppressing the combination explosion of the solution and fixing the variable δ _ik accompanying the expansion of the integer condition interval By partially performing the above, it is possible to make a production plan at a high speed with almost no deterioration of the optimality.

  In the optimum solution calculating step (S204), it is preferable to calculate an optimum solution that minimizes the evaluation function by the mixed integer programming method because a strict optimum solution can be obtained for a given problem. . Mixed integer programming is a problem in which the condition that the value must be an integer is added to some of the variables of a problem (linear programming problem) in which the objective function and constraint expression are expressed linearly (mixed integer) This is a method for calculating an exact solution of a planning problem.

  An object of the present invention is to supply a storage medium storing software program codes for realizing the functions of the above-described embodiments to a system or apparatus, and store the computer (CPU or MPU) of the system or apparatus in the storage medium. Needless to say, this can also be achieved by reading and executing the program code.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention. As a storage medium for supplying the program code, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) operating on the computer based on the instruction of the program code, etc. However, it is needless to say that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion is performed based on the instruction of the program code. It goes without saying that the CPU or the like provided in the board or the function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

  Next, a specific example of the production planning method to which the present invention is applied will be described in more detail. In the following, as an example of creating a production plan in a manufacturing process that processes a product with the same attribute in a lot under a certain constraint condition in a manufacturing plant that produces multiple types of products, the steel production plan in the metal product manufacturing industry Explains how to plan.

  In the order information input unit 102, plan target order data shown in Table 1 is acquired. As the product category of the production product model, three types of steel output components and four types of passing process patterns are considered, and a total of 12 combinations of steel output components and passing process patterns are considered. The occurrence rate of the refining process differs for each combination of the steel output component and the passing process pattern. For example, the production type of the steel output component A and the passing process pattern 100 (hereinafter A_100) has a gas process occurrence probability of 0.3, a correction process occurrence probability of 0.1, and a maintenance process occurrence probability of 0.1. It shows that there is. The order matrix goes back from the refining process to the upper process on the basis of the delivery date. Row) and the date of steel delivery deadline (column).

Next, the constraint equation setting unit 103 sets the constraint equation for equipment and delivery date. The tapping quantity is limited, another tapping quantity S _k day of the k day restricted represented by the following formula (3). Here, S_max represents the upper limit of steel capacity for one sunrise.

Approval frame x _{i, j by} production type on day k, steel output amount C _{i, k of} steel output component i and day k, steel type i, process pattern J (= 1, 2,... J [i]) _{, k} and the kth day, the sum of the bill surplus materials β _{i, k} of the steel output component i is expressed by the relationship of the following equation (4). Here, J [i] is the number of types of process patterns of component i.

It is not necessary to start the steel as per the date of the steelmaking request in the custom matrix, and the actual steelmaking may be made in time for the steelmaking request date. A certain amount of steel at sunrise includes those for different steelmaking dates. Approval frame x _{i, j, k by} production type of k-day, output steel component i, process pattern j is output steel by production type on day k, output steel component i, process pattern j, output date t desire Daily appropriated frame x _{^t i, j, ^t,} is expressed by the following formula (5) as the cumulative value in the planning period _q (between K day).

The restriction to produce steel within 5 days before and after the delivery date is expressed as follows. ref _{i, j, t} is a steel output request amount of a steel output component i, a process pattern j, and a steel output request date t.

Since the process load depends on the occurrence rate of the process, the process load y _{l, k} of the k-th day and the process number l is the allocation frame x _{i, of} the k-th day, the steel output component i, and the process pattern j according to the production type _. It is related by the following equation (8) by _{j, k} and the production type model r _{i, j, l,} which is the process occurrence rate of the steel output component i, the process pattern j, and the process number l.

  Here, I is the number of types of steel output components. In this embodiment, l = 1 represents gas processing, l = 2 represents correction processing, and l = 3 represents maintenance processing. The following formula (9) is intended to level the process load, and is a constraint formula that the moving average of the process load for three days does not exceed the process capability upper limit value.

Lot Size LOT_SIZE is determined by tapping the amount and number of lots, the k date, the tapping amount C _ik of tapping component i, the k date under with lot number [delta] L _ik of tapping component i (10) Are related by In this embodiment, the lot size is 200 tons.

The following formula (11) indicates whether or not there is a steel output of the steel output component i on the kth day. The δ _ik if steel is out of tapping component i in the k-th day take the 1, and take a 0 otherwise. However, the maximum value of the steel output amount C _ik is M. That is, Formula (11) formulates the following Formula (12).

Next, in the evaluation function setting unit 104, the evaluation function is set as shown in the following expression (13) using the variable _δik .

Next, the optimal solution calculation unit 105 calculates a solution that satisfies the constraint equations (3) to (11) and minimizes the evaluation function (13). First, if the variable _δik on the _0th to 2nd days is relaxed to a non-integer and the variable _{δik on} and after the 3rd day is relaxed to a non-integer, the plan shown in Table 2 is obtained. Since the variable δ _ik of the A grade on day 0 was found to be 0, it was fixed to 0, and the whole period was optimized by relaxing the variable δ _ik from the 0th to 3rd days to an integer interval and the 4th day onwards. When calculated, the results shown in Table 3 are obtained. Since the variable δ _ik of the B grade of the first day and the C _grade of the first day was found to be 0, it was fixed to 0, and the variable δ _ik after the 0th to 4th days was relaxed to a non-integer interval. The total planning period is optimized (results are shown in Table 4). Such processing is repeated until all the variables δ _ik become integers.

  Tables 5 and 6 are examples of steel production plans. Each row after the second row in Table 5 represents the daily steel production amount of one steel type, Table 6 represents each day's steel production plan amount for one product type, and Table 6 It is planned to produce 100 tons of steel on the first day.

  In FIG. 4, the 3-day moving average value of the process load in an Example is shown for every day. It can be seen that the process load does not exceed the capacity value.

  Further, FIG. 5 shows the cumulative value of the order matrix and the production type allocation frame in the embodiment. It can be seen that there is no preceding or delayed steel that deviates significantly from the date of request for steel production.

  In the production planning method to which the present invention is applied, a production plan is automatically drafted for a plurality of orders as shown in Table 1 under the constraint conditions such as equipment and delivery date. I was able to.

It is a figure which shows schematic structure of the production plan planning apparatus which concerns on embodiment. It is a flowchart which shows the production plan planning method by the production plan planning apparatus which concerns on embodiment. It is a flowchart which shows the process sequence in an optimal solution calculation step. It is a characteristic view which shows the 3-day moving average value of the process load in an Example for every day. It is a characteristic view which shows the cumulative value of the order matrix and the allocation frame classified by manufacture kind in an Example.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Order information storage database 102 Order information input part 103 Constraint expression setting part 104 Evaluation function setting part 105 Optimal solution calculation part 106 Output / display part S201 Order information reading step S202 Constraint expression setting step S203 Evaluation function setting step S204 Optimal solution calculation Step S205 Output / Display Step S301 Initialization Step S302 Relaxation Problem Creation Step S303 Relaxation Optimal Solution Calculation Step S304 Integer Determination Step S305 Restriction Condition Change Step

Claims (10)

In a production plant that produces a plurality of types of products, a production plan planning device for planning a production plan for processing products with the same attribute in batches,
A database that stores multiple order information;
Input means for fetching the plurality of order information from the database;
Based on the order information fetched by the input means, a constraint expression setting means for setting a constraint expression using the variable x representing equipment and delivery date constraints;
Evaluation function setting means for setting an evaluation function expressed using a variable δ which is a subset of the variable x;
An optimal solution for calculating the value of the variable x that is optimal by maximizing or minimizing the value of the evaluation function under the condition that the constraint equation is satisfied and the value of the variable δ is an integer of 0 or 1 A calculation means;
An output display means for outputting and displaying a production plan composed of operating conditions corresponding to the value of the variable x calculated by the optimum solution calculating means.   2. The production plan drafting apparatus according to claim 1, wherein the evaluation function is a sum of the variable δ of 0 or 1 representing the presence / absence of manufacturing by manufacturing date or manufacturing time and by type.   The optimal solution calculation means partially relaxes the condition that the variable δ is an integer of 0 or 1, and sets the constraint equation under the condition that a part of the value of the variable δ is a non-integer. A process of calculating a real value of the variable x that is satisfied and is optimized by maximizing or minimizing the value of the evaluation function, and 0 value among the variables δ belonging to the manufacturing time in which an integer condition is provided for the variable δ 3. The production planning apparatus according to claim 2, wherein the process of fixing a part or all of the variables δ having 0 to 0 is repeated until all the variables δ become integer values.   The optimal solution calculation means satisfies the constraint equation using mixed integer programming, and optimizes the evaluation function value by maximizing or minimizing the value. The production planning device according to the item. In a production plant that produces multiple types of products, a production plan drafting method for drafting a production plan for processing products with the same attribute in batches,
An order information storage step for storing a plurality of order information in a database;
Order information input step for fetching the plurality of order information from the database;
A constraint equation setting step for setting a constraint equation using the variable x representing the facility and delivery date constraint based on the order information captured in the input step;
An evaluation function setting step for setting an evaluation function expressed using a variable δ that is a subset of the variable x;
An optimal solution for calculating the value of the variable x that is optimal by maximizing or minimizing the value of the evaluation function under the condition that the constraint equation is satisfied and the value of the variable δ is an integer of 0 or 1 A calculation step;
A production plan drafting method comprising: an output display step for outputting and displaying a production plan composed of operating conditions corresponding to the value of the variable x calculated in the optimum solution calculating step.   6. The production plan planning method according to claim 5, wherein the evaluation function is a sum of the variable δ of 0 or 1 that represents the presence or absence of manufacturing by manufacturing date or manufacturing time and by type.   In the optimal solution calculation step, the condition that the variable δ is an integer of 0 or 1 is partially relaxed, and the constraint equation is satisfied under the condition that a part of the variable δ is a non-integer. A process of calculating a real value of the variable x that is optimized by maximizing or minimizing the value of the evaluation function, and having a zero value among the variables δ belonging to the manufacturing time in which an integer condition is provided for the variable δ The production planning method according to claim 6, wherein the process of fixing a part or all of the variables δ to 0 is repeated until all the variables δ become integer values.   8. The optimal solution calculation step according to claim 5, wherein the constraint equation is satisfied using a mixed integer programming, and the value of the evaluation function value is maximized or minimized. The production planning method described in the paragraph. In a production plant that produces multiple types of products, it is a program for creating a production plan for processing products with the same attributes in batches.
Order information storage processing for storing a plurality of order information in a database;
Order information input processing for fetching the plurality of order information from the database;
Based on the order information captured in the order information input process, a constraint expression setting process for setting a constraint expression using a variable x representing a facility and a delivery date constraint;
An evaluation function setting process for setting an evaluation function represented using a variable δ which is a subset of the variable x;
An optimal solution for calculating the value of the variable x that is optimal by maximizing or minimizing the value of the evaluation function under the condition that the constraint equation is satisfied and the value of the variable δ is an integer of 0 or 1 Calculation process,
A program for causing a computer to execute an output display process for outputting and displaying a production plan including an operation condition corresponding to the value of the variable x calculated by the optimum solution calculating means.   A computer-readable storage medium having recorded thereon the program according to claim 9.

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