JP4843201B2 - Information processing apparatus, information processing method, and program - Google Patents

Description

  The present invention relates to a technique for calculating an optimization problem for obtaining an optimal solution from a solution space composed of combinations of how values are assigned to variables.

  Conventionally, in the production of a plate-shaped steel plate (including a coil-shaped steel plate) (hereinafter simply referred to as a product), as shown in FIG. 13, a coil-shaped steel plate (hereinafter referred to as a base material) is cut by a cutting device ( In many cases, final products P1 to P4 are manufactured by cutting the base material in the width direction using the slitter 1203 and cutting in the longitudinal direction using the cutting device (leveler) 1201. Each part 1204 of the base material divided by the leveler is called a divided base material. On the other hand, in the process of determining the cutting method, after first determining how to cut the base material in the longitudinal direction using the cutting device (leveler) 1201, the cutting is performed in the width direction using the cutting device (slitter) 1203. Often decides how to do.

  In addition, when the product is allocated to the base material, it is desirable to plan so that the product can be manufactured with a yield as high as possible. For example, Patent Document 1 discloses a method for calculating a product yield plan with a high yield as an optimal solution. Further, constraint propagation technology is known as an algorithm for solving such a problem. For example, the constraint propagation technique disclosed in Non-Patent Document 1 is a technique for increasing search efficiency when solving a constraint satisfaction problem (including an optimization problem). During the solution of the constraint satisfaction problem, when the domain of a variable x (a set of possible values) is reduced, the domain of another variable y is reduced via the constraint including the variable x. The domain of other variables is further reduced through the constraint involving the variable y. The same thing happens in sequence. For example, assume that there are variables x, y, and z, and the respective domains are {1, 2}, {1, 2,..., 10}, {1, 2,. Assume that 5x + y ≦ 15 (constraint 1) and y ≧ 2z (constraint 2) are imposed as constraints. When the domain of the variable x changes from {1,2} to {2} (that is, when x = 2), 6, 7, 8, 9, 10 are removed from the domain of y via constraint 1 The domain of y changes from {1, 2,..., 10} to {1, 2,. Further, via constraint 2, 3, 4, and 5 are removed from the z domain, and the z domain changes from {1, 2,..., 5} to {1, 2}. As an effect of the constraint propagation technique, as a variable domain is reduced through a constraint as described above, another variable domain is reduced, so that the search tree is originally searched. Branches that could possibly be removed are cut off, the search space is reduced, and the search time is expected to be shortened as a result.

Japanese Patent No. 3039348 Kimiko Kusakari, 3 others, “Use of Constraint Propagation Technology as an Optimization Foundation”, November 9, 2000, 12th RAMP Symposium of the Operations Research Society of Japan, p. 53-60, Internet <URL: HYPERLINK "http://www.e-optimization.com/resources/uploads/RAMPdoc.pdf" http://www.e-optimization.com/resources/uploads/RAMPdoc.pdf>

  However, the invention disclosed in Patent Document 1 targets only one base material of a product, and cannot allocate a product allocation method for a plurality of base materials. Therefore, even when there are multiple base materials that can be used for product allocation on the day, it is not possible to determine an optimal product allocation method that can secure a high yield across the multiple base materials. However, there is still room for development in determining the optimal product allocation method in accordance with the above.

  Therefore, the present invention provides an information processing apparatus, an information processing method, and a program capable of determining a product allocation method across a plurality of base materials and planning a product allocation method in accordance with the actual situation of a product manufacturing site. The purpose is to provide.

In order to achieve such an object, the information processing apparatus of the present invention includes either one of the number of products to be allocated to each usage division matrix or the cutting pattern of each usage division matrix, and one or more Solution search processing means for performing solution search processing of a solution space including a set of combinations of values assigned to the variables, the number of divisions of the base material being included, and the solution search processing means includes the solution space In the solution search process, a value satisfying a constraint condition that the total width of each product allocated to each use division base material is equal to or less than the width of the corresponding base material is assigned to the variable, and the solution search process The means further includes a minimum production order days as the variable, and first assigns a value of a maximum number of days of a predetermined minimum production order days included in the initial information, and then decreases the assigned value in the direction of decreasing the assigned value. To the order of days assigned a value, it determines a value to first satisfy the constraint condition corresponding to the minimum production order of days, and the accumulated value of the ship of each product until the minimum production order number of days corresponds Products A value that satisfies a constraint condition that the value is equal to or less than the total value of the number of items is assigned to the variable.

The information processing method of the present invention is an information processing method by an information processing apparatus, wherein either the number of products to be allocated to each usage division matrix or the cutting pattern of each usage division matrix, and one or Each product that is assigned to each of the used divided base materials when executing solution search processing of a solution space that includes a number of divisions of a plurality of base materials as a variable and includes a set of combinations of values assigned to the variables A value satisfying the constraint that the total width is equal to or less than the width of the corresponding base material is assigned to the variable, the minimum production order days are included as the variable, and the predetermined minimum production order days included in the initial information assigned to the beginning value of the maximum number of days, then assign the value in the direction to decrease the value assigned to said minimum production order of days, satisfying the constraint condition corresponding to the minimum production order of days to first Determined, and, assigning a value to satisfy the minimum production order the sum less is that the constraints number of threads of the products accumulated value of ship amounts of each product corresponds to the number of days in the variable It is characterized by.

  According to a first aspect of the program of the present invention, a computer is caused to execute the information processing method.

  According to a second aspect of the program of the present invention, the function of the information processing apparatus is executed by a computer.

According to the present invention, provision method of the product is determined over between multiple base material, it becomes possible to determine the product allocation method conforming to actual conditions of the manufacturing site of the product, a variable (minimum production order days ) In the direction of decreasing the solution space, it is possible to detect a solution that has as many minimum production order days as possible, and as much space as possible until the next product manufacture (cutout operation). It becomes.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments to which the invention is applied will be described in detail with reference to the accompanying drawings. In the following description, “solving a problem” means “deciding how to assign values to variables for all variables appearing in the problem while observing the constraints to be satisfied”. That is, when one way of assigning values to all variables is determined, one solution is obtained.

FIG. 1 is a block diagram showing a functional configuration of an information processing apparatus according to an embodiment of the present invention.
As illustrated in FIG. 1, the information processing apparatus 100 according to the present embodiment has an initial information storage unit 101, a constraint condition derivation unit 102, a solution search processing unit 103, an optimal solution detection unit 104, and an output as functional configurations. A control unit 105 is provided.

  The initial information storage unit 101 stores initial information input by a user using an input unit such as a keyboard. Specific examples of this initial information include, for example, the number of base materials that can be used on the day, the width and length of each base material, the number of products to be manufactured, the upper and lower limits of the width of each product and the length of each product. Etc.

  Based on the initial information recorded in the initial information storage unit 101 and the search processing result of the solution search processing unit 103 (to be described later), the constraint condition deriving unit 102 is, for example, the constraint conditions (1) to (24) to be described later. Various constraints are derived. The solution search processing unit 103 performs a search, determines how to assign values to variables for some of the variables, and passes the determined assignment results of values to some of the variables to the optimal solution detection unit 104.

  The optimal solution detection unit 104 causes the value of a predetermined objective function to be the largest for variables whose values are not determined based on the result of assignment of values to some variables, which is the search result of the solution search processing unit 103. A method of assigning a correct value is searched for, and a value combined with the method of assigning the value to the variable determined by the solution search processing unit 103 is detected as an optimal solution. The output control unit 105 causes the optimum solution detected by the optimum solution detection unit 104 to be output using an output unit such as a display panel.

  FIG. 2 is a diagram showing a system configuration of the information processing apparatus 101 according to an embodiment of the present invention. The information processing apparatus 101 according to the present embodiment can be configured by a PC (personal computer) or the like as described below.

  A system bus 200 is a transmission path for transmitting data and control information between units. Each unit present in the housing of the information processing apparatus is connected by a system bus 200. Hereinafter, each unit will be described. A central processing unit (hereinafter referred to as a CPU) 201 performs various controls and operations of the information processing apparatus, and performs the constraint condition derivation unit 102, the solution search processing unit 103, the optimal solution detection unit 104, and the output control unit 105 in FIG. Takes the function corresponding to.

  A random access memory (hereinafter referred to as RAM) 202 functions as a main memory of the CPU 201, a storage area for an execution program, an execution area for a program, and a data area, and also has a function corresponding to the initial information storage unit 101. A read-only memory (hereinafter referred to as ROM) 203 is a basic program for controlling each unit in the information processing apparatus, that is, BIOS (Basic Input / Output System), information necessary for operating the information processing apparatus, and the like. Remember.

  A unit group (hereinafter simply referred to as FDD) 204 that performs data input / output performs data input / output of a removable external storage medium such as a flexible disk or a CD-ROM. A network interface (hereinafter simply referred to as NETIF) 205 is connected to an external network via a modem 206 described later or connected to a LAN 207 described later. The NETIF 205 performs control for performing data transfer between information processing apparatuses via the network and diagnoses connection status.

  The modem 206 is a device for connecting an external network and the information processing apparatus via a telephone line, and includes a modem and a terminal adapter for ISDN connection. The LAN 207 is a network system such as Ethernet (R). The information processing apparatus according to the present embodiment is connected to an external network using a communication device such as a router or a gateway connected on the modem 206 or the LAN 207, and enables data transmission / reception with the external apparatus.

  A video RAM (hereinafter referred to as VRAM) 208 develops image data to be displayed on a CRT 209 (to be described later) and controls display. The CRT 209 is a display device such as a display. The CRT 209 may be included in the information processing apparatus, or may be connected to the outside thereof.

  A keyboard controller (KBC) 210 controls input signals from the keyboard (KB) 211 and the mouse 212. The KB 211 is a keyboard for the user of the information processing apparatus to perform an input operation. The mouse 212 is a pointing device for a user of the information processing apparatus to perform an input operation. Each of the keyboard 211 and the mouse 212 may be included in the information processing apparatus, or may be connected to the outside.

  A hard disk drive (HDD) 213 is used to store application programs and various data. The application program refers to a software program for causing the information processing apparatus to execute the information processing method according to the present embodiment. A configuration in which the information processing apparatus obtains the application program via a data transmission medium such as an external network or a data recording medium such as a CD-ROM is also included in the scope of the technical idea of the present invention.

  A controller (IOC) 214 can perform input / output control of information with respect to an externally connected printer (PRT) 215, scanner 116, and the like. Although not shown in the figure, the IOC 214 can perform input / output control of information with, for example, an HDD or an MO drive connected to the outside in addition to the printer 215 and the scanner 216.

  FIG. 3 is a diagram schematically showing a state in which the product is attracted to the base material. In the following, as shown in FIG. 3, Mj (j = 1, 2, 3,..., M) is a base material that can be used on the day, and Mjk ( k = 1, 2, 3,..., n). In FIG. 3, MjW represents the width of the base material Mj, MjL represents the length of the base material Mj, and PiW represents the width of the product Pi.

  FIG. 12 is a diagram showing that a variable (number of strips) is given to a set of divided base material and product. A variable representing the number of products Pi (i = 1, 2, 3,..., L) assigned to the divided base material Mjk is expressed as PMjki.

  In FIG. 3, with respect to the base material M1, two split base materials (M11, M12) are obtained from the base material M1 by dividing the base material M1 into two parts in the longitudinal direction using a leveler which is a cutting device. For the base material M2, the base material M2 is equally divided into six parts in the longitudinal direction using a leveler, so that six base materials M2 (M21, M22, M23, M24, M25, M26) are divided from the base material M2. Shows a state where is obtained.

  In the cross section of the solution search process of the present embodiment, for the base material M1, all the split base materials (M11, M12) of the base material M1 are used split base materials. At least one product is assigned to each of M11 and M12. Similarly, for the base material M2, among the split base materials of the base material M2, M21, M22, and M23 are used split base materials, so at least one product is allocated to each of the split base materials M21, M22, and M23. It is done. In the example of FIG. 3, four products P1 are assigned to the divided base material M11 and the divided base material M12 (PM111 = PM121 = 4, PM112 = PM122 = 0), and the divided base material M21 and the divided base material Five strips of product P2 are allocated to M22 (PM211 = PM221 = 0, PM212 = PM222 = 5), and one strip of product P1 and three strips of product P2 are allocated to the divided base material M23 (PM231 = 1). , PM232 = 3).

Next, the operation of the information processing apparatus according to the present embodiment will be described.
First, the user inputs initial information to the information processing apparatus 100 using an input unit such as a keyboard. As described above, the initial information includes the number of base materials that can be used on the day, the width and length of each base material, the product type, the width of each product, and the upper and lower limits of the product length. And shipping schedule information of each product. A part of the initial information in the present embodiment is specifically shown below. In addition, instead of the upper limit value and the lower limit value of the lengths of the products P1 and P2, the maximum value and the minimum value of the outer diameters of the products P1 and P2 when the products P1 and P2 are coiled may be input. In this case, it is assumed that the thicknesses and inner diameters of the products P1 and P2 are constant.
・ Number of base materials: 2 (M1, M2)
・ M1 width: 1200mm
・ M1 length: 300m
・ M2 width: 1100mm
・ M2 length: 660m
・ Product type: 2 (P1, P2)
・ P1 width: 300mm
・ P2 width: 220mm
・ Upper limit of P1 length: 150m
・ Lower limit of P1 length: 100m
-Maximum length of P2: 120m
・ Lower limit of P2 length: 80m

  FIG. 8 is a diagram showing an example of shipping schedule information. In the shipping schedule information shown in FIG. 8, the shipping schedule dates for the products P1 and P2 are determined. That is, for the product P1, 8 on the current day (days "0"), 1 after 1 day (days "1"), 0 after 2 days (days "2"), 0 after 3 days (days) 3 ") is set to 2 and 4 days later (days" 4 "), and 0 is scheduled to be shipped, and for product P2, 12 on the day (days" 0 "), 1 0 after days (days “1”), 3 after 2 days (days “2”), 0 after 3 days (days “3”), 0 after 4 days (days “4”) The planned shipment quantity is determined.

Subsequently, the initial information storage unit 101 stores the input initial information. Next, the solution search processing unit 103 executes solution search processing by a branch and bound method. A solution space that is a target of the solution search process of the solution search processing unit 103 is shown in FIGS. The solution space shown in these is also called a search tree. In this solution search processing, as shown in FIGS. 9 and 10, solution search is performed in the following variable order (a) to (j).
(A) Total number of divided base materials, (b) Base material flag of base material M1, (c) Base material flag of base material M2, (d) Number of base material M1 splits, (e) Base material M2 (F) number of divided base materials used for base material M1, (g) number of used base materials for base material M2, (h) minimum number of production order days, (i) maximum number of production order days, (j) item number

  Each of the variables (a) to (j) is set for the information processing apparatus 100 in advance, and the search order of each variable is also determined according to the priority order. This is set for the search process.

  Next, a method for solving the constraint satisfaction problem by the solution search processing unit 103 will be described. FIG. 11 is a diagram illustrating the relationship between the variables (a) to (j), the reference area, the use area, the yield, and the like and the constraint conditions. In FIG. Variables that appear in the condition are marked with a circle. In this constraint satisfaction problem, the variables (a) to (j) and other variables are subjected to the constraint conditions shown in FIG. 11 and given to the variables (a) to (j). Find the solution by assigning the value in the given domain to a variable.

-Determination of the total number of split base materials used-
Next, a solution to the constraint satisfaction problem according to the present embodiment will be described with reference to the flowcharts of FIGS. 4 to 7 are flowcharts showing the flow of operations of the information processing apparatus according to the present embodiment.

  First, the solution search processing unit 103 determines the value of a variable (total number of divided base materials used). In the present embodiment, the smallest value (= 1) among the given domains for the variable (the total number of divided base materials used) is set first, and then the values are sequentially set in the direction of increasing the value. (Step S401). Here, it is assumed that “5” is set as the value of the variable (total number of divided base materials used).

  In the solution search process of the present embodiment, as described above, the solution search process is performed in a direction in which the value assigned to the variable (total number of divided base materials used) is increased. In other words, if a solution is detected by searching for a solution from a place where the total number of used divided base materials is small, the solution becomes a solution that takes the smallest possible number of used divided base materials in the solution space. Become. Accordingly, it is possible to detect a solution that reduces the product inventory as much as possible.

-Determination of base material-
Subsequently, the solution search processing unit 103 determines the maximum index value of the base material to be used from the base materials M1 to Mn that can be used on the day. Try the values from 1, 2, ... Mn in ascending order as the values assigned to the maximum index value of the base material to be used. Here, it is assumed that the maximum index value is determined to be “2”. Next, the solution search processing unit 103 determines the use base material flags of the base materials M1 and M2 corresponding to an index value equal to or less than the maximum index value. Specifically, the value of the used base material flag of the base material M2 having the maximum index value is “1”. Next, with respect to the base material having an index value less than the maximum index value, the use base material flag value “1” is tried first, and then “0” is tried in order of increasing index value. Since the maximum index value is now M2, only M1 corresponds to the base material of the index value less than the maximum index value. Next, while determining whether or not to use the base materials M1 and M2 for product production, all the base material flags of the base materials M3 to Mm corresponding to an index value larger than the maximum index value are set to “0”. (Step S402).

  If “0” is set in the use base material flag, no product is allocated to the corresponding base material in step S409, and neither of the products P1 and P2 is produced from the base material. On the other hand, if “1” is set in the use base material flag, at least one of the products P1 and P2 is assigned to the corresponding base material in step S409. Here, it is assumed that “1” (used) is set for both the variable (used base material flag (M1)) and the variable (used base material flag (M2)).

-Determination of the number of divisions for each base material-
Subsequently, the solution search processing unit 103 determines a variable (the number of divisions of the base material M1) indicating the number of divisions of the base material M1 (step S403). The following constraints (1) and (2) are imposed on the variables (the number of divisions of the base material M1).
Constraint (1) “Division number constraint”: Number of divisions of base material M1 ≦ Maximum number of divisions of base material M1 (= 3)
Constraint (2) “Length constraint”: number of divisions of base material M1 × lower limit value of product P1 ≦ length of base material M1 ≦ number of divisions of base material M1 × upper limit value of length of product P1 , The domain of the variable (number of divisions of the base material M1) is due to pruning in the constraint propagation technology,
Variable (number of divisions of base material M1) ∈ [2, 3]
Limited to

  In the present embodiment, the minimum value “2” in the domain is first selected as the value of the variable (number of divisions of the base material M1), and then the value is sequentially selected in the direction of increasing the value. Here, it is assumed that “2” is selected as the value of the variable (number of divisions of the base material M1). The maximum number of divisions of the base material M1 is numerical information included in the initial information.

Subsequently, the solution search processing unit 103 determines a variable (the number of divisions of the base material M2) indicating the number of divisions of the base material M2. The following constraints (3), (4), and (5) are imposed on the variable (number of divisions of the base material M2).
Constraint (3) “Division number constraint”: Number of divisions of base material M2 ≦ Maximum number of divisions of base material M2 (= 8)
Constraint (4) “Length constraint”: number of divisions of base material M2 × lower limit value of product P1 ≦ length of base material M2 ≦ number of divisions of base material M2 × upper limit value of length of product P1 Condition (5) “length constraint”: number of divisions of base material M2 × lower limit value of product P2 ≦ length of base material M2 ≦ number of divisions of base material M2 × upper limit value of length of product P2

That is, the domain that the variable (number of divisions of the base material M2) can take is due to pruning in the constraint propagation technique,
Variable (number of divisions of base material M2) ∈ [6]
Limited to Therefore, the solution search processing unit 103 sets “6” as the value of the variable (the number of divisions of the base material M2). The maximum division number of the base material M2 is numerical information included in the initial information.

−Determining the number of split base materials used for each base material−
Subsequently, the solution search processing unit 103 sets the number of used divided base materials for each base material Mm (step S405). First, the solution search processing unit 103 sets the number of used divided base materials of the base materials (base materials M3 to Mm) whose base material flag is “0” in step S402 to “0”. Subsequently, the solution search processing unit 103 sets a variable (the number of used divided base materials of the base material M1) indicating the number of used divided base materials of the base material M1. The following constraints (6), (7), and (8) are imposed on the variable (the number of divided base materials used for the base material M1).
Constraint (6) “Definition of use base material flag”: If variable (use base material flag of base material M1) = “1”, variable (number of use base materials for base material M1) ≧ 1
Constraint (7) “Definition of the total number of split base materials used”: variable (total number of split base materials used) = sum of the number of base split base materials used for all base materials = variable (number of base split base materials used for base material M1) + Variable (number of base materials used for base material M2)
Constraint (8) “Total base material number upper limit constraint”: Variable (number of used base materials of base material M1) ≦ variable (number of base materials M1)
That is, the domain of the variable (the number of divided base materials used for the base material M1) is obtained by pruning in the constraint propagation technology.
Variable (number of divided base materials used for base material M1) ∈ [1, 2]
Limited to

  In this embodiment, the maximum value “2” in the domain is first assigned as the value of the variable (the number of divided base materials used for the base material M1), and then the values are sequentially assigned in the direction of decreasing the value. Here, it is assumed that “2” is assigned as the value of the variable (the number of used divided base materials of the base material M1).

Subsequently, the solution search processing unit 103 determines a variable (the number of used divided base materials of the base material M2) indicating the number of used divided base materials of the base material M2. The following constraints (9), (10), and (11) are imposed on the variable (the number of divided base materials used for the base material M2).
Constraint (9) “Definition of use base material flag”: If variable (use base material flag of base material M2) = “1”, variable (number of base materials used for base material M2) ≧ 1
Constraint (10) “Definition of total number of used divided base materials”: variable (total number of used divided base materials) = total number of used divided base materials for all base materials = variable (number of used divided base materials for base material M1) + Variable (number of base materials used for base material M2)
Constraint condition (11) “upper limit number of divided base materials”: variable (number of used divided base materials of base material M2) ≦ variable (number of divided base materials M2)
That is, the domain of the variable (the number of divided base materials used for the base material M2) is obtained by pruning in the constraint propagation technology.
Variable (number of base materials used for base material M2) ∈ [3]
Limited to Accordingly, the solution search processing unit 103 assigns “3” as the value of the variable (the number of used divided base materials of the base material M2).

  Next, the solution search processing unit 103 sets a variable (number of stripes) corresponding to a divided base material that is not used to “0” (step S406). Now, "2" as the value of the variable (number of divisions of the base material M1), "2" as the value of the variable (number of division base materials used of the base material M1), as the value of the variable (number of divisions of the base material M2) " Since “3” is assigned as the value of “6” and the variable (the number of divided base materials used for the base material M2), the variables corresponding to the split base material M24, the split base material M25, and the split base material M26 (the number PM241) ), Variable (strip number PM 251), variable (strip number PM 251), variable (strip number PM 252), variable (strip number PM 261), and variable (strip number PM 262) are assigned "0".

-Determination of minimum production order days-
Subsequently, the solution search processing unit 103 determines a value of a variable (minimum production order days) (step S407). As for the variable (minimum production order days), the maximum number of days (= 5) of the predetermined minimum production order days included in the initial information is assigned first, and then values are sequentially assigned in the direction of decreasing the value. Here, it is assumed that “1” is selected as the value of the variable (minimum production order days).

  Here, the minimum production order days is the product P1 corresponding to “how many days ahead” of the condition that the planned shipment quantity of each product P1, P2 up to the minimum number of days ahead in the shipping schedule information of FIG. , P2 is common day information. Note that the minimum production order days being “0” means that the planned shipment amount of each product for the day is produced. Further, in the solution search process of the present embodiment, the solution space search process is performed in the direction of decreasing the variable (minimum production order days). In this case, the solution search is performed from the place where the minimum production order days are large, and when the solution is detected, the solution takes the highest value of the minimum production order days in the solution space. Therefore, by searching the solution space in a direction to reduce the variable (minimum production order days), the minimum production order days will be as many as possible, and as a result, as many days as possible will be kept until the next product production (cutout work). It is possible to detect the solution to be obtained.

-Determination of maximum production order days-
Subsequently, the solution search processing unit 103 determines a value of a variable (maximum production order days) (step S408). As for the variable (maximum production order days), the minimum number of days (= 1) of the predetermined maximum production order days included in the initial information is assigned first, and then values are sequentially assigned in the direction of increasing the value. Here, it is assumed that “2” is selected as the value of the variable (maximum production order days).

  Here, the maximum number of production order days corresponds to “how many days ahead” of the condition that, on the shipment schedule information in FIG. 8, only the scheduled shipment quantities of the products P1 and P2 up to how many days ahead should be produced. This is the number of days information common to the products P1 and P2. Further, in the solution search process of the present embodiment, by performing the solution space search process in the direction of increasing the variable (maximum production order days) from the value of the minimum production order days, the number of days of product allocation between products is determined. It is possible to detect the optimal solutions that are aligned. By the way, in this embodiment, the solution search process is performed in the variable order of variables (total number of divided base materials used), variables (minimum production order days), and variables (maximum production order days). This optimizes user requests according to the priorities of "I want to reduce product inventory as much as possible", "I want to leave as much time as possible until the next product manufacture (cut-out work)", and "I want to keep the number of days allocated between products" This is to reflect in the solution.

FIG. 5 is a flowchart showing the detailed operation of the solution search processing unit 103 in steps S401, S402, S403, S405, S407, and S408 of FIG.
First, the solution search processing unit 103 determines whether or not the domain of the currently searched variable is an empty set (step S501), and if the domain is an empty set, backtracks to the next higher level variable. (Step S502). Here, “backtracking” is to return a target to which a value is assigned to a variable located closer to the root in the search tree.

  On the other hand, if the domain of the currently searched variable is not an empty set, one value is selected (step S503), and the selected value is set as the variable value (step S504). Subsequently, the solution search processing unit 103 performs constraint propagation on the selected value through the constraint condition related to the variable, and determines that a contradiction has occurred when the domain of any other variable becomes empty ( In step S505), the selected value is removed from the domain (step S507). Thus, numerical values that contradict the constraints are removed from the domain and the domain is reduced. On the other hand, if the variable does not contradict the related constraint conditions, the solution search processing is shifted to a variable located on the far side from the root in the search tree (step S506).

-Determination of number of articles-
As described above, each variable ((a) total number of used divided base materials, (b) used base material flag of base material M1, (c) used base material flag of base material M2, and (d) split of base material M1. (E) number of divisions of base material M2, (f) number of divisional divisions of base material M1, (g) number of divisional divisions of base material M2, (h) minimum production order days, (i) maximum When the value of production order days) is determined, the solution search processing unit 103 searches for a set of values of variables (number of items) related to each product on each usage split base material that maximizes the yield (step S409). ). This optimization is performed in a situation where the values of variables other than the number of stripes are fixed. Then, the optimum solution detection unit 104 detects a solution that achieves the best yield among the solutions obtained by this optimization trial as the optimum solution.

Now, two usage division base materials (M11, M12) are determined for M1, and three usage division base materials (M21, M22, M23) are determined for M2. Therefore, the solution search processing unit 103 executes solution search processing for each variable (number of lines) of PM111, PM112, PM121, PM122, PM131, PM132, PM211, PM212, PM221, PM222, PM231, and PM232. In this embodiment, it is assumed that an optimal solution is detected when each variable (number of lines) takes the following values, and the constraint satisfaction related to the variable (number of lines (PMjki)) is satisfied using the following example. From the solution of the problem to the solution of the optimization problem will be described with reference to the flowcharts of FIGS. FIG. 7 is a flowchart showing details of step S409 in FIG. 4, and FIG. 6 is a flowchart showing details of step S701 in FIG.
Article number PM111: 4, Article number PM112: 0, Article number PM121: 4, Article number PM122: 0, Article number PM211: 1, Article number PM212: 3, Article number PM221: 0, Article number PM222: 4, Article number PM231: 0, Article number PM232: 4

In the solution search processing unit 103, the following constraint conditions are imposed on each variable (number of lines).
Constraint (12) “Definition of assignment flag”: If the variable (assignment flag) of the product Pi in the base material Mj is “1”, at least one product Pi is included in any of the divided base materials in the base material Mj. Is assigned, and if it is “0”, the product Pi is not assigned to any of the divided base materials in the base material Mj.
Constraint (13) “Strip number 0 constraint”: If the number of divided base materials used in the base material Mj is “0”, the number of strips assigned to the base material Mj is “0”.
Constraint (14) “Definition of use width”: use width of divided base material Mjk = number of products P1 in divided base material Mjk × width of product P1 + number of products P2 in divided base material Mjk × product P2 Width constraint condition (15) “base material width constraint”: use width of divided base material Mjk ≦ base material width constraint condition of base material Mj (16) “definition of production amount”: production amount of product Pi = divided base material 11 Number of product Pi in product + number of product Pi in divided base material + ... + product number of product Pi in divided base material 23 Restriction (17) “Definition of production upper limit value”: Production of product Pi Quantity upper limit = Scheduled shipment quantity limit for product Pi for minimum production order days (18) “Definition of production lower limit value”: Production lower limit value for product Pi = Scheduled shipment quantity for product Pi for maximum production order days Constraint (19) “Production Upper / Lower Constraint”: Product Pi Lower Production ≤Product Pi Production ≤Product Pi Upper Production Value Constraint (20) “Definition of reference area”: Reference area = width of base material M1 × length of base material M1 × number of used base materials of base material M1 / number of base materials of base material M1 + base material M2 Width × base material M2 length × number of base material M2 used divided base materials / number of base material M2 split base materials +... + Base material Mm width × base material Mm length × base material Mm Number of used divided base materials / number of divided base materials of base material Mm (21) “Definition of used area”: used area = (length of base material M1 × width of product P1 / number of divided base materials of base material M1) ) X number of strips [1,1,1] + (length of base material M1 × width of product P2 / number of base materials of base material M1) × number of strips [1,1,2] + ... + ( Length of base material M2 × width of product P1 / number of base materials M2 divided) × number of strips [2,3,1] + (length of base material M2 × width of product P2 / partition of base material M2) Number of base materials) x number of strips [2, 3, 2]
Constraint (22) “Yield Definition”: Yield (Objective Function Value) = Used Area / Reference Area Constraint (23) “Yield Min Constraint”: Yield (Objective Function Value) ≧ Yield Minimum Value Constraint (24): Yield (objective function value)> known best solution yield (objective function value)

  First, the solution search processing unit 103 determines whether or not the values of all the strips (MP111, MP112, MP121, MP122, MP211, MP212, MP221, MP222, MP231, and MP232) have already been determined (step S601). . If the solution search processing unit 103 determines in this determination that the values of all the strips have not yet been determined, the variable having the smallest number of domain elements among the strips for which no value has been determined (the number of strips) Is selected (step S602).

  In this embodiment, excluding PM112 and PM122 (assuming that the allocation flag of the product P2 in the base material M1 is “0 (not allocated)”), the variable with the smallest domain (number of lines) is PM232. Accordingly, the solution search processing unit 103 preferentially determines the value of the variable (strip number PM232) over other variables (strip number PMjki).

  Subsequently, the solution search processing unit 103 selects the smallest value from the domain for the variable (strip number PM232) (step S603) and sets it as the value of the variable (strip number PM232) (step S604). Next, the solution search processing unit 103 determines whether or not the value set for the variable (the number PM232) contradicts the constraint conditions (12) to (23 (or 24)) (step S605). If the value set for the variable (strip number PM232) contradicts the constraint conditions (12) to (23 (or 24)), the set value is removed from the domain of the variable (strip number PM232) (step S606), If the domain is an empty set, the solution search processing unit 103 determines whether or not backtracking is possible. If backtracking is possible, the solution search processing unit 103 backtracks to the next higher level variable (number). (Steps S607, S608, S610). In this case, since the value set for the variable (number PM232) is consistent with the constraints (12) to (23 (or 24)), the solution search processing for the next level variable (number) from step S601 is performed. Transition. If the domain determined to be an empty set in step S607 is the highest level variable, it is determined that backtracking is not possible, and the solution search process is terminated as “no solution” (steps S608 and S609). . As a determination method of occurrence of contradiction in step S605, it is determined that a conflict has occurred when the domain of any variable becomes an empty set as a result of assigning the value to the variable and performing constraint propagation. .

  In step S608, it has been described that if the domain is an empty set, it is backtracked to a variable (number of items) located closer to one variable (maximum production order days) in the search tree. If it is a variable (strip number) located closest to the variable (maximum production order days) in the tree (here, variable (strip number PM112)), it is treated as no solution in step S609, and the direction of No in step S702 It will branch to.

  Thereafter, the solution search processing unit 103 preferentially determines a value from a variable (number of items) having a small number of values included in the domain.

By the above procedure, a solution consisting of a combination of values assigned to each variable is calculated. As shown in FIGS. 9 and 10, the solutions calculated here are listed below.
-Total number of divided base materials used: 5
・ Base material flag (M1): 1
・ Base material flag (M2): 1
-Number of divisions (M1): 2
-Number of divisions (M2): 6
・ Number of divided base materials (M1): 2
・ Number of divided base materials (M2): 3
・ Minimum production order days: 1
・ Maximum production order days: 2
・ Article number (PM111): 4
-Article number (PM112): 0
-Article number (PM121): 4
-Article number (PM122): 0
・ Article number (PM211): 0
-Article number (PM212): 5
-Article number (PM221): 0
・ Article number (PM222): 5
-Article number (PM231): 1
-Article number (PM232): 3

Next, the optimal solution detection method in this embodiment will be described.
First, as described above, when the solution search processing unit 103 calculates the solution of the constraint satisfaction problem through the processing of steps S601 to S609 in FIG. 6 (step S701), the optimal solution detection unit 104 has a solution. (Step S702), the solution calculated first is not subject to the constraint (26), and the solution = “known best solution”, the objective function value (yield) based on the solution = “ It is unconditionally recorded in the RAM 202 by the optimum solution detecting unit 104 as a known best solution objective function value "(step S703).

  As described above, once the “known best solution” and “the objective function value of the known best solution” are once recorded in the RAM 202, the objective function value of the solution is “the known best solution” in the subsequent solution search processing. The constraint condition (24) that the value must be larger than the “objective function value of the solution of” is further derived by the constraint condition deriving unit 102 (step S704). Accordingly, the next solution calculated in step S701 is a solution having a higher objective function value than the initially calculated solution (known best solution). In this case, in step S704, “the known best solution” and “the objective function value of the known best solution” are updated to numerical values based on the next solution, and the contents of the constraint condition (24) are also updated in the same manner. . This processing flow is executed until the optimization problem shown in FIG. 7 is solved, and the “known best solution” recorded in the RAM 202 until the end is determined as the optimum solution (step S706).

The user can grasp at least the following items by outputting the above-mentioned optimum solution to the display panel or the like.
・ Which base material should be used among the base materials that can be used on the day ・ How many base materials should be divided? ・ How many of the divided base materials should be used as split base materials for each base material ・ Each use How many products are allocated to each divided base material

  In this embodiment, the solution search process includes a solution space including, as a variable, the number of strips of each product assigned to each use-divided base material of a plurality of base materials. Therefore, according to the present embodiment, even when there are a plurality of base materials that can be used on the day, it is possible to calculate a product allocation method that can secure a high yield across the base materials, and manufacture of the products A product allocation plan can be made in accordance with the actual situation at the site.

  In this embodiment, only the value of the variable (number of lines) is changed to perform local optimization of the yield. This model is not an optimization problem as a whole, but is regarded as a constraint satisfaction solution. Can do. Therefore, this model is used for the purpose of obtaining one constraint satisfaction solution. An embodiment in which an objective function (yield) is further given to this model and a search for a solution with a high yield is continued until the objective function value exceeds a certain threshold value is also conceivable. It is also conceivable that a time limit is set for the optimization, and a solution having the maximum value of the objective function is detected as an optimal solution among the solutions obtained by the solution search process within the time limit.

The following is a supplementary explanation of the variables that appeared in this model.
・ Reference area: There is only one reference for the entire problem. Represents the total area of the usage split base material.
・ Number of divided base materials used: Present for each base material. Of the divided base materials of the base material, the number of the divided base materials used is represented.
-Number of divisions: exists for each base material. Indicates how many base materials are divided in the length direction.
・ Used area: There is only one area for the entire problem. Represents the total area of products produced.
・ Yield: There is only one problem in the whole problem. Represents the ratio of the total area of the product to be produced to the total area of the usage split base material.
・ Use width: Exists for each divided base material. Represents the total product width produced from the split base material.
・ Strip number: It exists for each divided base material and each product. Indicates the number of strips that cut the product from the divided base material.
・ Production lower limit: Exists for each product. This represents the planned shipment amount for the minimum production days of the product.
-Minimum production order days: There is only one for the entire problem. It shows how many days the production volume of each product should meet the planned shipment volume. That is, each product is produced so as to satisfy the planned shipment amount for the minimum production order days. The minimum production days are not different for each product, but are common to each product.
・ Production upper limit: It exists for each product. This represents the planned shipment quantity for the maximum production order days for the product.
・ Maximum production order days: There is only one for the entire problem. It shows how many days the production amount of each product can only meet the planned shipment amount. In other words, each product will be produced only at the planned shipment quantity for the maximum production order days. The maximum production days are not different for each product, but are common to each product.
-Use base material flag: present for each base material. Indicates whether to use the base material.
-Total number of split base materials used: There is only one for the entire problem. Represents the total number of split base materials used.
-Production volume: exists for each product. Represents the production volume of the product.
-Allocation flag: exists for each base material and each product. Indicates whether the product is produced from the base material.

  In the present invention, a variable representing the cutting pattern of the divided base material may be used for each divided base material instead of the variable (the number PMjki). The cutting pattern is a combination pattern of products having a use width within a range that fits within the base material width. For example, if the base material width is 1200 mm and the product types are 300 mm and 220 mm, there are 16 cutting patterns as shown in Table 1.

It is the block diagram which showed the function structure of the information processing apparatus which concerns on one Embodiment of this invention. It is the figure which showed the system configuration | structure of the information processing apparatus which concerns on one Embodiment of this invention. It is the figure which showed typically the state which attracted the product to the base material. It is the flowchart which showed the flow of operation | movement of the information processing apparatus which concerns on one Embodiment of this invention. It is the flowchart which showed the flow of operation | movement of the information processing apparatus which concerns on one Embodiment of this invention. It is the flowchart which showed the flow of operation | movement of the information processing apparatus which concerns on one Embodiment of this invention. It is the flowchart which showed the flow of operation | movement of the information processing apparatus which concerns on one Embodiment of this invention. It is a figure showing an example of shipping schedule information. It is the figure which showed typically the solution space used as the object of a solution search process. It is the figure which showed typically the solution space used as the object of a solution search process. It is the figure which showed the relationship between a variable and a constraint condition. It is a figure which shows that the variable (number of articles) is given with respect to the group of a division | segmentation base material and a product. It is the figure which showed the manufacturing process of the general plate-shaped rope board product.

Explanation of symbols

101 Initial Information Storage Unit 102 Constraint Condition Deriving Unit 103 Solution Search Processing Unit 104 Optimal Solution Detection Unit 105 Output Control Unit

Claims (16)

Either one of the number of products to be allocated to each usage division base material or the cutting pattern of each usage division base material, and the number of divisions of one or more base materials as variables, and assigning values to the variables Solution search processing means for performing solution search processing of a solution space consisting of a set of combinations of
In the solution search processing of the solution space, the solution search processing means has a value that satisfies a constraint condition that a total width of each product allocated to each use division base material is equal to or less than a width of the corresponding base material. In addition to assigning to the variable, the solution search processing means further includes a minimum production order days as the variable, first assigns a value of the maximum number of days of the predetermined minimum production order days included in the initial information, and then assigns the value to be assigned. A value is assigned to the minimum production order days in a decreasing direction, a value that satisfies the constraint condition corresponding to the minimum production order days is determined to be the first value , and the planned shipment amount of each product up to the minimum production order days An information processing apparatus is characterized in that a value that satisfies a constraint condition that a cumulative value of is less than or equal to a total value of the number of corresponding products is assigned to the variable.   The solution search processing means further includes, as the variable, a total number of used divided base materials that is the total number of the used divided base materials, and assigns a value to the total number of used divided base materials in a direction to increase the value to be assigned. The information processing apparatus according to claim 1.   The information processing apparatus according to claim 2, wherein the solution search processing unit further assigns a value to the minimum production order days after the total number of divided base materials used. The solution search processing means further includes a maximum production order days as the variable , first assigns a value of a minimum number of days of the predetermined maximum production order days included in the initial condition, and then increases the value to be assigned. Assigning a value to the maximum production order days, determining a value that satisfies the constraint condition corresponding to the maximum production order days first, and accumulating the estimated shipping amount of each product up to the maximum production order days The information processing apparatus according to claim 1, wherein a value satisfying a constraint condition that a value is equal to or greater than a total value of the number of applicable products is assigned to the variable. The solution search processing means further includes the maximum production order days as the variable, assigns a value to the maximum production order days in a direction to increase the assigned value, and each product up to the maximum production order days Is assigned to the variable a value that satisfies the constraint that the cumulative value of the planned shipping quantity is equal to or greater than the total value of the number of applicable products, and further, the total number of divided base materials used and the minimum production order days 4. The information processing apparatus according to claim 2 , wherein a value is assigned to the maximum production order days later.   The solution search processing means assigns a value to a variable including at least the minimum production order days other than the streak variable or the cutting pattern variable, fixes the previously assigned variable, 6. The information processing apparatus according to claim 1, wherein the value of the streak variable or the cutting pattern variable is changed so as to take a value with the largest area yield of the product with respect to the material.   It further comprises optimum solution detection means that uses area yield as an objective function, and continues to search for a solution with a high objective function value until the objective function value exceeds a given threshold value or a given time elapses. The information processing apparatus according to any one of claims 1 to 6. An information processing method by an information processing apparatus,
Either one of the number of products to be allocated to each usage division base material or the cutting pattern of each usage division base material, and the number of divisions of one or more base materials as variables, and assigning values to the variables Satisfying the constraint that the total width of each product allocated to each usage-divided base material is less than or equal to the width of the corresponding base material when executing solution search processing of a solution space consisting of a set of combinations And assigning a value to be assigned to the variable, including a minimum production order number of days as the variable, assigning a value of a maximum number of days of a predetermined minimum production order number included in the initial information first, and then decreasing the assigned value. assigning a value to a minimum production order number of days, the constraints corresponding to the minimum production order number of days determined in the first value to be satisfied, and, the ship of each product to the minimum production order dates An information processing method the value of the cumulative value to satisfy the constraint condition to the effect that less total value of the number of threads of the relevant product, characterized in that assigned to the variable.   The solution search process further includes, as the variable, the total number of used divided base materials, which is the total number of used divided base materials, and assigns a value to the total number of used divided base materials in a direction to increase the value to be assigned. The information processing method according to claim 8.   The information processing method according to claim 9, wherein the solution search process further assigns a value to the minimum production order days after the total number of divided base materials used. The solution search process further includes a maximum production order number of days as the variable, first assigns a value of a minimum number of days of a predetermined maximum production order number included in the initial condition, and then increases the assigned value in the direction of increasing the assigned value. Assign a value to the production order days, determine a value that satisfies the constraint condition corresponding to the maximum production order days first, and cumulative value of the planned shipment amount of each product up to the maximum production order days 10. The information processing method according to claim 8, wherein a value satisfying a constraint condition that is equal to or greater than a total value of the number of applicable products is assigned to the variable. The solution search process further includes the maximum production order days as the variable, assigns a value to the maximum production order days in a direction to increase the value to be assigned, and each of the products up to the maximum production order days. Assign a value that satisfies the constraint that the cumulative value of the planned shipping quantity is greater than or equal to the total value of the number of applicable products to the variable, and after the total number of divided base materials and the minimum production order days The information processing method according to claim 9 , wherein a value is assigned to the maximum production order days.   The solution search processing is performed by assigning a value to a variable including at least the minimum production order days other than a streak variable or a cutting pattern variable, and fixing the variable previously assigned the value, The information processing method according to any one of claims 8 to 12, wherein a value of the streak variable or the cutting pattern variable is changed so as to take a value having the largest area yield of the product with respect to.   14. The search for a solution with a high value of the objective function is continued until the area yield is an objective function, and the value of the objective function exceeds a given threshold value or a given time elapses. The information processing method according to any one of the above.   The program for making a computer perform the information processing method of any one of Claims 8 thru | or 14.   The program for making a computer perform the function of the information processing apparatus of any one of Claims 1 thru | or 7.

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