JPH06219518A - Simulation device for determining container loading method - Google Patents

Abstract

PURPOSE:To provide a simulation device for determining a container loading method where the load of an operator is reduced by automating the parameter selection in the trial and error method, and at the same time, the loading method of a relatively heavy and large product such as steel product into a container can be easily considered. CONSTITUTION:A simulation device is provided with a simulation parameter storing device 7 where the information concerning a plurality of parameters are stored, a parameter condition storing device 8 where the information on the parameters to be determined by repeating the simulation is stored, and a result evaluating part 6 where the combination of a plurality of parameter values is successively changed, and the simulation is realized by the simulation executing part 5 in each case, and the combination of the parameter values when the average weight loading ratio of the total containers finally becomes most efficient.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an average weight of all containers when transporting objects to be transported in which individual products such as steel products are relatively heavy and large and each has a different shape. Loading condition, that is, the product loading condition at the workplace so that the average value of the ratio of the weight of the transported object loaded on each container to the loadable weight of each container loaded with the transported object is maximized under certain conditions The present invention relates to a simulation device for automatically determining.

[0002]

2. Description of the Related Art Conventionally, steel products are often transported by so-called bulk loading in which products are directly loaded on ships or trucks. Therefore, conventionally, little is known about the methodologies for loading and transporting steel products in containers.

In general, when an industrial product is transported by a container, for example, an electric home appliance and the like are individually packaged, and therefore, it is relatively easy to load the product into the container. However, in order to efficiently load products into a container when transporting steel products in a container, under the fixed conditions such as the same destination and the same delivery date, each product with a different size has a fixed volume called a container. How to stack efficiently in containers, and how much each product weighs more than general products, and how different weights of products are stacked to a value close to the maximum loadable weight of a container, and the average weight of all containers It is an important issue to improve the loading rate or to satisfy both of these points at the same time.

However, the solutions to these problems differ depending on the characteristics of the products manufactured every moment, that is, the size, weight, delivery date of the products, and the like. Therefore, it is an effective method to determine the loading method by computer simulation using the data of the product to be loaded into the container loading work site at a certain time.

However, by the time the loading method is decided,
It is necessary to repeatedly execute the simulation by changing various conditions when simulating the loading method, that is, variously changing simulation parameters. Regarding the method of determining simulation parameters by iterative execution of such simulation, “Application of simulation to production and logistics efficiency improvement” (Management System, Vol. 1,
No.2, February 1992, p132-p140), a human judges the simulation result and the behavior of the solution and repeatedly executes the simulation by changing the simulation parameter variously. A method based on the And-Error method is introduced. However, in this method, a person judges and selects all of the values of the parameters for the judgment of the simulation result and the next execution of the simulation.

[0006]

When the method of loading a container on a container is re-examined at intervals of several hours or days using the conventional simulation technique, it is necessary to execute the simulation each time. In the case of the above simulation, it was necessary to change the simulation parameters many times by the try-and-error method before deciding the loading method for the container. For this reason, it is difficult to perform a simulation study unless you are an expert.
There is also a problem that it takes time and labor.

The present invention has been made in view of the above circumstances. By automating the selection of parameters in the try-and-error method which has been conventionally adopted, the labor of the operator can be reduced and the steel products can be manufactured. It is an object of the present invention to provide a container loading method determination simulation device capable of easily studying a method of loading a relatively heavy and large product in a container as described above.

[0008]

SUMMARY OF THE INVENTION According to the present invention, when a plurality of types of objects to be transported having different weights and sizes are loaded and transported in a container having a fixed capacity, a fixed size and an upper limit of a load weight, the container is transported. In a container loading method determination simulation apparatus that determines a method of loading a plurality of containers by combining a plurality of objects to be transported by simulation, a first storage unit that stores conditions regarding each usable container, and a plurality of types of transportation targets. A second storage means for storing conditions relating to the object; a simulation parameter storage means for storing a plurality of parameters indicating conditions for loading the object to be transported into each container stored in the first storage means; Possible for each of a plurality of parameters stored in the simulation parameter storage means And parameter condition storage means for storing a range of the simulation parameter storing means and the parameter condition storage means and the initial condition setting means for setting a condition related parameters from the outside and, first and second
The conditions regarding the container and the transportation target object stored in the storage means are read, a simulation for loading the transportation target object in the container is executed according to the parameters stored in the simulation parameter storage means, and the transportation target object is loaded. A simulation execution unit that obtains a simulation execution result including an average weight loading rate that represents an average value of the weight ratios of the objects to be transported that are loaded with respect to the loadable weight of each container, and a simulation execution result by the simulation execution unit. Simulation result storage means for storing, result history storage means for sequentially storing the combination of the average weight loading rate stored in the simulation result storage means and the parameter value stored in the parameter condition storage means, Each time the simulation by the simulation execution means is finished, the simulation repetition status and the average weight loading rate stored in the simulation result storage means are evaluated according to a predetermined law, and the value of the parameter used for the next simulation to be executed. The result evaluation which changes the value of the parameter storage means to obtain the combination of the above, causes the simulation executing means to repeatedly execute the simulation, and finally obtains the combination of the parameter values that maximizes the average weight loading ratio of all containers. And means.

[0009]

According to the present invention, the value of the parameter to be determined by repeatedly executing the simulation is automatically and sequentially changed according to a predetermined law, and the average weight loading ratio finally becomes the maximum efficiency. A combination is required.

[0010]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below in detail with reference to the drawings showing the embodiments thereof. In the following examples, steel products are targeted as an example of the object to be transported, but the present invention is not limited to this.

FIG. 1 is a block diagram showing the overall construction of an embodiment of a container loading method determination simulation device (hereinafter referred to as the device of the present invention) according to the present invention. In FIG. 1, reference numeral 1 denotes a container loading method determination simulation apparatus of the present invention, to which a host computer 2 for giving information from the outside is connected.

The device 1 of the present invention is roughly composed of an input / output device indicated by reference numeral 3 and respective processing devices indicated by reference numerals 4 to 6 (initial condition setting section 4, simulation executing section 5). , Result evaluation unit 6), and the storage devices (simulation parameter storage device 7, parameter condition storage device 8, scheduled delivery list storage device 9, product inventory list storage device 10) indicated by reference numerals 7 to 13. It is composed of a container inventory list storage device 11, a simulation result storage device 12, a result history storage device 13) and the like.

Each of the processing units indicated by reference numerals 4 to 6 may be composed of an individual CPU, or one CPU may be used in common. Further, each of the storage devices indicated by reference numerals 7 to 13 may be composed of an individual storage device, for example, a memory, a magnetic disk, a hard disk, or the like, and one storage device also serves as the storage device. Good.

Further, the carry-in scheduled goods list storage device 9 and the product inventory list storage device 10 function as a second storage means for storing conditions relating to steel products as a plurality of types of objects to be transported, and the container inventory list storage device. Reference numeral 11 functions as a first storage unit that stores conditions regarding each usable container.

The input / output device 3 is, for example, a keyboard, a mouse, a printer, a CRT display, etc.
In order for the (simulator) to input various information and commands to the device 1 of the present invention, the device 1 of the present invention
It is provided for outputting various information from.

The simulation parameter storage device 7 stores simulation parameters required when the simulation executing unit 5 executes the simulation process, such as the simulation start date, end date, container loadable capacity, minimum required load, It stores information such as the temporary storage capacity of products in the work space, the capacity of the sorting container storage space, the shipping pitch, the amount of one shipment, and the stacking size condition.

The parameter condition storage device 8 can have a parameter name designated by an operator and a parameter name of the parameter stored in the simulation parameter storage device 7 whose value is to be determined by simulation. The range of values (maximum value and minimum value) and the unit amount for increasing or decreasing the parameter value are stored.

The planned carry-in product list storage device 9 is connected to the host computer 2, and stores a list of planned carry-in products transmitted from the host computer 2. Specifically, information such as scheduled delivery date and time, product number, size, weight, delivery date, shipping destination, product inspection end flag, and the like for each product is stored.

The product inventory list storage device 10 and the container inventory list storage device 11 are temporary storage devices that the simulation execution unit 5 accesses at any time during the execution of the simulation processing. In the product inventory list storage device 10, a list of products temporarily placed in the workplace without being loaded in a container due to a delivery deadline or a product inspection incomplete, etc. It is stored in the format of. Further, in the container inventory list storage device 11,
It stores the shipping destination, delivery date, possible load capacity, current load capacity, loaded product number, progress status of shipment, etc. for each container.

The simulation result storage device 12 stores a simulation result list of the total number of containers sorted during the simulation period, the total weight of products loaded in the containers, the average weight loading rate of all the containers, and the like. .

Here, the average weight loading rate will be described. The average weight loading rate is an index showing how much product can be loaded in each container when a simulation is performed using a certain parameter, and is expressed by the following equation (1).

[0022]

[Equation 1]

The result history storage device 13 stores a history of all combinations of parameter values used in the simulation and the simulation results each time the simulation executing section 5 executes the simulation process.

FIG. 2 is a flowchart showing a processing procedure by the device 1 of the present invention. In the processing of steps S1 to S10 shown in FIG. 2, step S1 is performed by the initial condition setting unit 4, step S2 is performed by the simulation execution unit 5, and other steps S3 to S9 are performed by the result evaluation unit 6. Executed respectively.

First, in step S1, the initial condition and the range of possible values of the simulation parameter are set by the initial condition setting unit 4. Specifically, for parameters that may be fixed values among the simulation parameters, the values are output from the initial condition setting unit 4 to the simulation parameter storage device 7. Also, regarding the parameters specified by the operator and to be determined by the simulation, the maximum value, the minimum value, and the unit amount for increasing / decreasing are set by the operator via the input / output device 3, so the initial condition setting The unit 4 outputs them to the simulation parameter storage device 7 and the parameter condition storage device 8.

At this time, with respect to the parameter designated by the operator as to be determined by simulation, the point of the combination of the respective minimum values is first set as the reference point. This reference point is to be compared with the average weight loading ratio of all containers finally obtained as a result of the simulation in the subsequent steps. Hereinafter, the simulation executing unit 5 repeatedly executes the simulation with the combination points of the parameters outside the reference point by the unit amount of each parameter as the search points sequentially, and the average weight loading rate of all the containers is most improved. The reference point is sequentially moved to the search point.

A schematic diagram of FIG. 3 shows an example of a case where there are two parameters to be determined in the search range. In FIG. 3, white circles indicate reference points and black circles indicate search points.

In step S2, the simulation executing section 5 inputs the product data stored in the carry-in scheduled goods list storage device 9 and, in accordance with the parameters stored in the simulation parameter storage device 7,
Furthermore, the product transfer to the container is simulated for each product while accessing the product inventory list storage device 10 and the container inventory list storage device 11 as needed. After the execution of this simulation, the simulation result is output from the simulation execution unit 5 to the simulation result storage device 12.

In step S3, the result evaluation section 6 reads the result of the average weight loading ratio of all the containers, which is the result parameter, from the simulation result storage device 12.

In step S4, the result evaluation section 6 determines whether or not the simulation has been performed for all the search points by referring to the result history storage device 13. At this time, the overlap of the search range due to the movement of the reference point is also considered.

An example of overlapping search ranges is shown in the schematic diagram of FIG. It should be noted that FIG. 4 shows a case where there are two parameters to be determined in all, as in the case of FIG. 3 described above.
Further, in FIG. 4, as in the case of FIG. 3 described above, white circles indicate reference points and black circles indicate search points.

In FIG. 4, if the reference point moves from the point Pi-1 to Pi, the search point at the point Pi is the point Pi-1.
It becomes three points of si1, si2, si3 excluding. Hereinafter, if all the searches have been completed, the process proceeds to step S5, and if not, the process proceeds to step S7.

In step S5, the result evaluation section 6 determines whether or not there is a search point with an improved simulation result among search points outside the reference point, and there is a search point with an improved simulation result. In case step
If not, the process proceeds to step S10. In step S10, the result evaluation unit 6 outputs the history of simulation results and the value of each parameter to the input / output device 3 assuming that the current reference point Pi is the final combination point of the parameters, and executes all processing. To finish.

In step S6, the result evaluation unit 6 finds the search point with the largest improvement from the search points with improved simulation results and sets it as the next reference point. Here, when moving from the current reference point Pi to the next reference point Pi + 1, a point satisfying the following formula is selected as the next reference point Pi + 1 among all search points sij at the current reference point Pi. To be done.

[0035]

[Equation 2]

In step S7, the result evaluation unit 6 determines the combination of the search point parameters used in the next simulation execution by referring to the result history storage device 13. At this time, as in step S4,
If there is a point for which simulation has already been executed due to overlapping search ranges, that point is not selected.

In step S8, the result evaluation section 6 changes the contents of the simulation parameter storage device 7 in steps.
Update to the value calculated in S7. In step S9, the result evaluation unit 6 outputs the simulation result of this time and the combination of the search point parameters to the result history storage device 13 and stores them.

Thereafter, after the processing is returned to step S2, the above processing is repeated until it is determined in step S5 that there is no search point that improves the simulation result.

The search for the simulation parameters and the movement of the reference point will be described with reference to the schematic diagrams of FIGS. It should be noted that FIGS. 5 to 8 below show a case where there are two parameters to be determined, as in the case of FIG. 3 described above. In addition, in FIGS. 5 to 8, the white circles indicate the reference points and the black circles indicate the search points, as in FIG. 3 described above.

Point of combination of each parameter (p1, p2)
Is a search point candidate at each intersection that divides the minimum value to the maximum value by a unit amount. FIG. 5 shows the result of simulation for search points s11 and s12 outside the initial reference point P1, which is a combination of the minimum values of the parameters, that is, the average weight loading rate of all containers is 60% at the search point s11. , s12
It shows that it has become 61%. In this case, the reference point P1
Since the search point s12 is the most improved compared to the average weight loading rate of 58% in the above, this point s12 is selected as the next reference point P2.

FIG. 6 shows the search point s at the new reference point P2.
Simulation results for 21 and s22 are 64%,
It shows that it has become 63%. In this case, the search point s21
Is selected as the next reference point P3.

Similarly in FIG. 7, the search point s32 is the next reference point P.
Indicates that it will be selected as 4. Hereinafter, the search and the movement of the reference point are repeated, and the simulation is performed until the final solution is reached. As a result, for example, the final solution as shown in FIG. 8 is obtained, and it becomes clear that the point P7 is a combination of parameters having the highest average weight loading rate. In addition,
In FIG. 8, it is assumed that the simulation is executed also at points other than the intersections, and the distribution of the results is displayed by contour lines.

In this way, when a combination of parameters having the highest average weight loading rate is obtained by repeating the simulation, the result is output to the input / output device 3 and the process is terminated.

[0044]

As described in detail above, according to the present invention,
Since the parameter selection in the conventional try-and-error method is automated, the labor of the operator is reduced and the method of loading a relatively heavy and large product such as a steel product into a container can be studied. It becomes easy to simulate.

[Brief description of drawings]

FIG. 1 is a block diagram showing the overall configuration of an embodiment of a container loading method determination simulation device according to the present invention.

FIG. 2 is a flowchart showing a processing procedure by the device of the present invention.

FIG. 3 is a schematic view exemplifying a case where there are two parameters to be determined in a search range of a combination of simulation parameters by the device of the present invention.

FIG. 4 is a schematic diagram illustrating a case where there are two parameters to be determined and the search ranges overlap.

FIG. 5 is a schematic diagram for explaining a search for a simulation parameter and a movement of a reference point by the device of the present invention.

FIG. 6 is a schematic diagram for explaining a search for a simulation parameter and a movement of a reference point by the device of the present invention.

FIG. 7 is a schematic diagram for explaining a search for a simulation parameter and a movement of a reference point by the device of the present invention.

FIG. 8 is a schematic diagram for explaining a search for a simulation parameter and a movement of a reference point by the device of the present invention.

[Explanation of symbols]

 2 host computer 3 input / output device 4 initial condition setting unit 5 simulation execution unit 6 result evaluation unit 7 simulation parameter storage device 8 parameter condition storage device 9 planned delivery list storage device 10 product inventory list storage device 11 container inventory list storage device 12 Simulation result storage 13 Result history storage

Claims (1)

[Claims] 1. A combination of a plurality of objects to be transported when a plurality of types of objects to be transported having different weights and sizes are loaded in a container having a fixed capacity and a fixed size and a maximum load weight In a container loading method determination simulation device that determines a method of loading a plurality of containers by simulation, a first storage unit that stores a condition regarding each usable container and a second storage unit that stores a condition regarding a plurality of types of objects to be transported. Storage means, a simulation parameter storage means for storing a plurality of parameters indicating conditions for loading the object to be transported in each container stored in the first storage means, and the simulation parameter storage means The range of possible values for each of the Parameter condition storage means, initial condition setting means for externally setting conditions relating to parameters in the simulation parameter storage means and the parameter condition storage means, and containers stored in the first and second storage means And a condition regarding the object to be transported, a simulation of loading the object to be transported in a container is executed according to the parameters stored in the simulation parameter storage unit, and the loadable weight of each container in which the object to be transported is loaded Simulation execution means for obtaining a simulation execution result including an average weight loading rate representing an average value of the weight ratios of the objects to be loaded on the vehicle, and a simulation for storing the simulation execution result by the simulation execution means. Result storage means, result history storage means for sequentially storing the combination of the average weight loading rate stored in the simulation result storage means and the parameter value stored in the parameter condition storage means, and the simulation execution Each time the simulation by the means is completed, the repeated condition of the simulation and the average weight loading rate stored in the simulation result storage means are evaluated according to a predetermined law, and the value of the parameter used in the simulation to be executed next is evaluated. Change the value of the parameter storage means to obtain a combination,
Container loading method determination, characterized by further comprising: result evaluation means for causing the simulation executing means to repeatedly execute the simulation and finally obtaining a combination of parameter values that maximize the average weight loading rate of all containers. Simulation device.