JPWO2018092305A1 - Manufacturing plan formulation device, production plan formulation method, and production plan formulation program - Google Patents

Abstract

In order to devise an appropriate manufacturing plan in a short time, the integer plan optimization calculation unit searches for a combination of products to be set in a manufacturing apparatus capable of setting a plurality of drawing numbers at the same time by the integer programming method (S10), and within the set time If the combination cannot be searched for (S12: No), the dynamic optimization calculation unit searches for a part of the combination of products that can be set in the manufacturing apparatus by the dynamic programming (S18). When the search in step S18 is performed, the integer plan optimization calculation unit excludes the products included in the combination searched by the dynamic optimization calculation unit 34, and the combination of products set in the manufacturing apparatus Are searched again by integer programming (S20).

Description

  The present invention relates to a production plan formulation device, a production plan formulation method, and a production plan formulation program.

  Traditionally, mass production has been the mainstream in manufacturing sites, where the same products flow in an orderly manner, but now that individual products have become more customizable, multi-product small-volume production has become mainstream. . In such a production site, a plurality of different types of products may be manufactured in one apparatus. In the case of such a device, it is desirable to set and operate the product as much as possible. However, the conditions of each product are complicated at the site of high-mix low-volume production, and the insight and experience of the workers at the site are It is difficult to find an appropriate combination of products to be set in one device in a situation where it depends.

Special table 2015-531161 gazette JP 2000-112505 A JP 2005-92726 A

  When obtaining an appropriate combination of products to be set in one apparatus, it is common to perform optimization calculation as numerical calculation (see, for example, Patent Documents 1 to 3). However, in the case of calculating an appropriate combination for setting in a device from a plurality of types of products, an appropriate solution may not be obtained when the number of combinations increases.

  In one aspect, an object of the present invention is to provide a manufacturing plan formulation device, a manufacturing plan formulation method, and a manufacturing plan formulation program that can quickly search for an appropriate combination of products to be set in a device. .

  In one embodiment, the production plan formulation device is a production plan formulation device that formulates a production plan for a plurality of types of products, and searches for a combination of products set in a device that can set a plurality of products at the same time by integer programming. A first search unit and a second search unit that searches for a combination of a plurality of types of products that can be set in the device by dynamic programming when the first search unit and the first search unit cannot search for the combination within a predetermined time. A search unit, and when the search is performed by the second search unit, the first search unit excludes products included in the combination searched by the second search unit and executes the search again. To do.

  An appropriate combination of products to be set in the apparatus can be searched in a short time.

It is a figure which shows roughly the hardware constitutions of the manufacturing plan formulation apparatus which concerns on one Embodiment. It is a functional block diagram of a manufacturing plan formulation device. It is a figure for demonstrating the formulation process of the manufacturing plan by a manufacturing plan formulation apparatus. It is a figure which shows an example of figure number data. It is a flowchart which shows an example of a process of a manufacturing plan formulation apparatus. It is a figure which shows an example of a correspondence analysis result. It is a figure which shows an example of the search result using a dynamic programming. It is a figure which shows an example of the search result using an integer programming. It is a figure which shows a modification.

  Hereinafter, an embodiment of a production plan formulation device will be described in detail with reference to FIGS.

  FIG. 1 shows a hardware configuration of a production plan formulation device 10 according to an embodiment. The manufacturing plan formulation apparatus 10 of the present embodiment obtains an appropriate combination of products to be set in a manufacturing apparatus in a situation where a plurality of different products are set in the same manufacturing apparatus and manufactured in a manufacturing site for multi-product low-volume production. In this way, it is a device that formulates a product manufacturing plan. It should be noted that a group of products manufactured with the same specification, that is, the same type of product, is hereinafter referred to as “drawing number”. The production plan formulation device 10 includes a PC (Personal Computer) and the like, and as shown in FIG. 1, a CPU (Central Processing Unit) 90, a ROM (Read Only Memory) 92, a RAM (Random Access Memory) 94, a storage unit ( Here, an HDD (Hard Disk Drive) 96, a display unit 93, an input unit 95, a portable storage medium drive 99, and the like are provided. Each component of the manufacturing plan formulation device 10 is connected to a bus 98. The input unit 95 includes a keyboard, a mouse, a touch panel, and the like, and the display unit 93 includes a liquid crystal display and the like. The user (operator) inputs figure number data as shown in FIG. 4 via the input unit 95 as information on a product (drawing number) to be manufactured using the manufacturing apparatus. In the manufacturing plan formulation device 10, a program (including a manufacturing plan formulation program) stored in the ROM 92 or the HDD 96, or a program (including a manufacturing plan formulation program) read from the portable storage medium 91 by the portable storage medium drive 99. ) Is executed by the CPU 90, the functions of the respective units shown in FIG. 2 are realized.

  FIG. 2 is a functional block diagram showing functions realized by the manufacturing plan formulation device 10 when the CPU 90 executes the program. As shown in FIG. 2, the production plan formulation device 10 includes an integer plan optimization engine 40, a dynamic optimization engine 30, a text analysis engine 20, and an input / output unit 50. The input / output unit 50 acquires figure number data (see FIG. 4) input by the user via the input unit 95 and inputs it to the integer plan optimization engine 40, the dynamic optimization engine 30, and the text analysis engine 20. Further, the input / output unit 50 acquires information (manufacturing plan) of combinations of products (drawing numbers) set in the manufacturing apparatus obtained by the integer plan optimization engine 40 and causes the display unit 93 to display the information.

  In this embodiment, as an example, a product is manufactured by setting a plurality of products in a manufacturing apparatus as shown in FIG. In this case, for example, when manufacturing a product having a total figure number a and a total product number b by using a predetermined number n of manufacturing apparatuses, the manufacturing plan formulation apparatus 10 indicates that “a product with the same figure number has a plurality of products. Assume that a combination of products set in the manufacturing apparatus is determined so that the constraint condition “does not cross over the manufacturing apparatus” is satisfied and the number of times of use m of the manufacturing apparatus is minimized.

  Here, the figure number data in FIG. 4 includes figure number text, product number, and set number data. The figure number text means identification information of the figure number, the number of products means the number of products included in each figure number, and the number of sets means the number of products that can be set in one manufacturing apparatus. When a product with a different drawing number is set in one manufacturing apparatus, the smallest number among the number of sets corresponding to the set drawing number is the number that can be set in one manufacturing apparatus.

  The integer plan optimization engine 40 of FIG. 2 includes a figure number information input unit 42, an integer plan optimization calculation unit 44 as a first search unit, and a calculation possibility determination unit 46. The figure number information input unit 42 acquires the figure number data input from the input / output unit 50 and inputs it to the integer plan optimization calculation unit 44. The integer plan optimization calculation unit 44 searches for a combination of products to be set in the manufacturing apparatus based on the figure number data of FIG. The integer plan optimization calculation unit 44 transmits the search result to the input / output unit 50 when the search is completed. The computability determination unit 46 determines whether the search by the integer plan optimization calculation unit 44 is completed within a predetermined time. When it is determined that the search has not been completed within a predetermined time, the computability determination unit 46 notifies the figure number information input unit 32 of the dynamic optimization engine 30 to that effect.

  The dynamic optimization engine 30 includes a figure number information input unit 32 and a dynamic optimization calculation unit 34 as a second search unit. The figure number information input unit 32 acquires the figure number data input from the input / output unit 50 and the figure number sort result input from the text analysis engine 20. Further, the figure number information input unit 32 receives the figure number data and the figure obtained when the integer plan optimization calculation unit 44 receives a notification from the calculation possibility determination unit 46 that the calculation cannot be completed within a predetermined time. The number sorting result is input to the dynamic optimization calculation unit 34. The dynamic optimization calculation unit 34 searches for a combination of products that can be set in one device by using dynamic programming, using the figure number data and the figure number sort result. As the dynamic programming, a so-called knapsack problem solving method or the like can be used. When the dynamic optimization calculation unit 34 performs a search using only the figure number sort result, the figure number data may not be input from the input / output unit 50 to the figure number information input unit 32. .

  The text analysis engine 20 includes a figure number text input unit 22, a correspondence analysis calculation unit 24, and a figure number sort unit 26. The figure number text input unit 22 extracts the figure number text from the figure number data input from the input / output unit 50 and inputs the extracted figure number text to the correspondence analysis calculation unit 24. When the correspondence analysis calculation unit 24 receives a notification from the calculation possibility determination unit 46, the correspondence analysis calculation unit 24 uses the text analysis method such as correspondence analysis to indicate the figure number text as coordinates and displays the analysis result that displays the position of the figure number as coordinates. It transmits to the figure number sort part 26. The figure number sorting unit 26 determines the search order from the analysis result of the figure number text using the solution of the traveling salesman problem, and uses the determined search order (the figure number sort result) as the figure number of the dynamic optimization engine 30. It transmits to the information input part 32.

(Processing of the manufacturing plan formulation device 10)
Next, the process of the manufacturing plan formulation apparatus 10 of this embodiment is demonstrated in detail, referring suitably to other drawings along the flowchart of FIG.

  Here, when a plurality of products are set in the same manufacturing apparatus, formulation of a set of products to be set (manufacturing plan) can be reduced to an optimization problem. As described above, the optimization problem is a problem for obtaining a combination of products to be set in the manufacturing apparatus so that the number of times the manufacturing apparatus is used is minimized. In this embodiment, it is assumed that there are a plurality of the same manufacturing apparatuses, and a plurality of types of products (a plurality of drawing numbers) can be set in the same manufacturing apparatus. In general, the drawing numbers that can be set in the same manufacturing apparatus are considered to have the same operating conditions of the manufacturing apparatus, but the details of the drawing numbers may be different. For example, the product size is different.

  In the case of products with different figure numbers that can be set in the same manufacturing apparatus, if the conditions that can be set differ, the optimization problem is often considered as a constraint condition. For example, as shown in FIG. 3, when manufacturing products with two different drawing numbers (01, 02), 12 drawing numbers (01) and 9 drawing numbers (02) are manufactured, It is assumed that six manufacturing apparatuses are used. In this case, the drawing number (01) is limited to the maximum number of products that can be input to the manufacturing apparatus (the number of sets in FIG. 4) is five, and the drawing number (02) is the maximum number of products that can be input to the manufacturing apparatus (set). If the number is limited to four, when these figure numbers are set in the same manufacturing apparatus, the number is set to the smaller number. Such operation varies depending on various sites and manufacturing apparatuses, but is considered as a constraint condition in optimization problems. With the number of drawings and the number of manufacturing apparatuses as described above, the optimization problem can be easily solved, such that all products can be manufactured by operating five manufacturing apparatuses.

  Further, it is assumed that the number of drawing numbers, the number of products, and the number of manufacturing apparatuses are further increased than the above example (for example, the total number of drawing numbers is 12 and the total number of products is 57). Even in this case, by using integer programming, which is one of the solutions for the optimization problem, it is possible to obtain in a short time that all the products can be manufactured by rotating 6 manufacturing apparatuses for 2 cycles. it can. In this case, the production plan formulation device 10 sets products so as to satisfy the constraint conditions in a total of 12 production devices, and leads to a solution that minimizes the total number of operations. In addition, if the manufacturing plan formulation apparatus 10 has a processing capability similar to that of a commercially available personal computer, a solution can be obtained in about a few minutes if the above-mentioned calculation is performed.

  On the other hand, when the number of figure numbers and the number of products are further increased, the total number of figure numbers is 18 and the total number of products is 81, the number of combinations is larger than the case of the total number of figure numbers 12 and the total number of products 57. Causes millions of times more information explosion. For this reason, it is impossible to obtain a solution using integer programming. For example, with a processing capacity comparable to that of a commercially available personal computer, a solution cannot be obtained even over several hours.

  In this way, if you try to solve combinatorial optimization with integer programming, you will be searching for a solution that satisfies the constraint conditions, so you can solve it as soon as the total number of figures and the total number of products change slightly. Disappear. At present, the quantity of figure numbers changes day by day in the field of high-mix low-volume production, so if you derive a solution using only integer programming, you can solve it in some cases but not in others. The actual on-site operation is difficult. Therefore, in the present embodiment, processing according to the flowchart of FIG. 5 is adopted.

  5 is started when the figure number data is input to the input / output unit 50 and the figure number data is transmitted to the engines 20, 30, and 40.

  First, in step S10 of FIG. 5, the integer plan optimization calculating unit 44 searches for an optimal solution to be set in the manufacturing apparatus as an integer plan problem. That is, the integer plan optimization calculation unit 44 searches for an optimal combination of products to be set in the manufacturing apparatus by the integer programming method.

  Next, in step S12, the calculation possibility determination unit 46 determines whether or not a solution is obtained within a set time (for example, within several minutes) in the process of step S10. If the determination in step S12 is affirmative, the process proceeds to step S24, and the integer plan optimization calculation unit 44 outputs a solution (a combination of products set in the manufacturing apparatus) to the input / output unit 50. The input / output unit 50 displays the solution on the display unit 93 when the solution is acquired. As described above, when the combination of products to be set in the manufacturing apparatus is displayed on the display unit 93, the entire process of FIG. Since the time until the solution is obtained by the integer programming method depends on the environment to be used (such as the specifications of the manufacturing plan formulation device 10), it is preferable to set the set time according to the environment.

  On the other hand, if the determination in step S12 is negative, it is determined to the correspondence analysis calculation unit 24 and the figure number information input unit 32 that the calculation possibility determination unit 46 has not been able to obtain a solution within a predetermined time. Notice. When the correspondence analysis calculation unit 24 receives the notification from the calculation possibility determination unit 46, in step S <b> 14, the correspondence analysis calculation unit 24 coordinates the figure number using the figure number text information input from the figure number text input unit 22. Here, in general, similar (similar) figure number texts are often assigned to similar figure numbers. The correspondence analysis calculation unit 24 displays the figure number text as coordinates using a text analysis technique such as correspondence analysis, and displays the position of the figure number as coordinates. FIG. 6 shows an example of the result of correspondence analysis. By this processing, the figure number text can be digitized. The correspondence analysis calculation unit 24 transmits the result of the correspondence analysis to the figure number sorting unit 26.

  Next, in step S <b> 16, the figure number sorting unit 26 determines a search order using a solution of the traveling salesman problem. Specifically, the figure number sorting unit 26 determines the search order along the order of similar figure number texts using the traveling salesman problem solution based on the coordinate values obtained in step S14. Note that the figure numbers may be grouped by multivariate analysis based not only on the text information of figure numbers but also on information such as product sizes that are originally digitized. In this case, since the grouped results can also be displayed in coordinates, the figure number sorting unit 26 can determine the product search order based on such coordinates. The figure number sorting unit 26 transmits the determined search order to the figure number information input unit 32. The figure number information input unit 32 transmits the search order received from the figure number sort unit 26 to the dynamic optimization calculation unit 34 when receiving a notification from the calculation possibility determination unit 46.

  Next, in step S18, the dynamic optimization calculation unit 34 searches for a combination of products that can be set in the manufacturing apparatus according to the search order using dynamic programming (by dynamic optimization). Here, as the dynamic programming, a so-called knapsack solution can be used. The knapsack problem is a method for solving the problem of how to combine products with different values and sizes into a knapsack and maximizing the value of the knapsack as a whole. It is. The feature of this method is that only items that can be packed in the knapsack are considered, and items that are not packed are not considered in the scope of the problem. For this reason, by regarding the knapsack as a manufacturing apparatus and the product packed in the knapsack as a product, a combination that maximizes the value of the product set in the manufacturing apparatus can be output without fail. Here, it is assumed that the dynamic optimization calculation unit 34 determines a combination of products to be set for one cycle of the manufacturing apparatus.

  Here, in general dynamic optimization, only the figure numbers that can be set in the manufacturing apparatus are preferentially determined, so there is no guarantee that an optimum solution will be obtained for the remaining figure numbers. Therefore, in the present embodiment, in the dynamic optimization, the similar drawing numbers are preferentially set in the manufacturing apparatus. As a result, the order in which the products are set is not complicated, it is possible to suppress a decrease in on-site operability, and to improve on-site work efficiency.

  The dynamic optimization calculation unit 34 transmits information on the combination of products set in one cycle of the manufacturing apparatus determined in step S18 to the diagram number information input unit 42. The figure number information input unit 42 transmits the received combination information to the integer plan optimization calculation unit 44.

  Next, in step S20, the integer plan optimization calculation unit 44 searches for a solution as an integer programming problem for the remaining figure numbers. In this case, the integer plan optimization calculation unit 44 manufactures the figure number (product) included in the figure number data except for the product set for one cycle of the manufacturing apparatus determined by the dynamic optimization calculation unit 34. Search for combinations to be set in the device using integer programming.

  Next, in step S22, the calculation possibility determination unit 46 determines whether or not a solution is obtained within the set time in the process of step S20. If the determination in step S22 is negative, the process returns to step S18, and the processes and determinations in steps S18, S20, and S22 are repeated. That is, in step S18, the dynamic optimization calculation unit 34 further searches for a combination of figure numbers (products) set in one cycle of the manufacturing apparatus. In step S20, the integer plan optimization calculation unit 44 Search for a combination that sets the remaining product (drawing number) in the manufacturing apparatus. In step S22, the calculation possibility determination unit 46 determines whether or not a solution is obtained within the set time in the process of step S20. As described above, in the present embodiment, while the determination in step S22 is denied, the process of reducing the number of drawings and the number of products is repeated in step S18 to a scale that can be finally solved as an integer programming problem. If the solution can be searched for in step S20, the determination in step S22 is affirmed, and in step S24, the integer plan optimization calculation unit 44 calculates the solution (search result of the combination of products set in the manufacturing apparatus). Output to the input / output unit 50. In this case, the input / output unit 50 causes the display unit 93 to display the search result. Here, the solution output from the integer plan optimization calculation unit 44 to the input / output unit 50 includes a search result in the dynamic optimization calculation unit 34. When the combination of products to be set in the manufacturing apparatus (manufacturing plan) is displayed on the display unit 93 as described above, the entire process of FIG.

  Hereinafter, as a specific example, a description will be given of an example in which a production plan is created when products having a total figure number of 16 and a total number of products of 75 as shown in FIG. 4 are set in six production apparatuses. In this example, as a result of searching for the optimal solution by integer programming (S10), no solution was found within the set time (S12: No). For this reason, the text information of the figure number information was analyzed, and a product that can be set in one cycle of six manufacturing apparatuses from similar figure numbers by dynamic programming was obtained (S14 to S18). As a result, 24 products (four figure numbers) as indicated by thick line frames in FIG. 7 were determined as products to be set in one cycle of six manufacturing apparatuses. Then, the solution was calculated | required by the integer programming problem with respect to the remaining 12 figure numbers (S20). As a result, the figure number indicated by the broken line frame in FIG. 8 is determined as the figure number set in the second cycle, and the figure number indicated by the thick line frame is determined as the figure number set in the third cycle. It took several minutes to obtain the above results. As described above, even if integer programming alone cannot solve the problem in a short time, the process of FIG. 5 is executed, so that a total of 16 product numbers and 75 products can be obtained in a total of 3 cycles. It can be obtained in a short time that it can be manufactured.

  As described above in detail, according to the present embodiment, the integer plan optimization calculation unit 44 searches for a combination of products to be set in a manufacturing apparatus capable of setting a plurality of drawing numbers at the same time by the integer programming method (S10). When the combination cannot be searched within the set time, the dynamic optimization calculation unit 34 searches for a part of the combination of products that can be set in the manufacturing apparatus by the dynamic programming (S18). When the search in step S18 is performed, the integer plan optimization calculation unit 44 excludes products included in the combination searched by the dynamic optimization calculation unit 34, and sets the products to be set in the manufacturing apparatus. The combination is searched again by integer programming (S20). As a result, even when formulating a production plan for products with a total figure number and total number of products that cannot be solved by integer programming alone, it is possible to reduce the number of An appropriate manufacturing plan can be formulated. In this case, since dynamic programming is used repeatedly and finally reduced to a scale that can be solved by integer programming, an appropriate manufacturing plan can be formulated in a short time regardless of the scale. it can.

  In the present embodiment, the dynamic optimization calculation unit 34 searches for a combination of products by dynamic optimization in accordance with the search order of products obtained from the correspondence analysis result of the figure number text. As a result, the order in which the products are set is not complicated, it is possible to suppress a decrease in on-site operability, and to improve on-site work efficiency.

  Further, in the present embodiment, when the integer plan optimization calculation unit 44 actually searches for a combination and cannot find a combination within the set time (S12: negative), the dynamic optimization calculation unit 34 However, it is supposed to search by dynamic programming. As a result, a search using dynamic programming can be performed only when an information explosion actually occurs.

  In the above embodiment, the case where the search using the dynamic programming is performed when the search using the integer programming is not actually performed within the set time has been described. However, the present invention is not limited to this. For example, when a condition that cannot be obtained unless a search by dynamic programming is used together is determined in advance, dynamic programming may be executed from the beginning when the condition is satisfied.

  In the above embodiment, each manufacturing apparatus in FIG. 3 may be integrated to form one manufacturing apparatus. That is, when one manufacturing apparatus has a plurality of divided parts (for example, stages), each part (stage) may correspond to each manufacturing apparatus in FIG. In this case, the “number of sets” shown in FIG. 4 means the number of products that can be set in each stage.

  In the above embodiment, the case where the knapsack problem solving method is adopted as the dynamic programming method has been described. However, the present invention is not limited to this, and other dynamic programming methods may be used. Further, the case of using the traveling salesman problem solving method when determining the search order has been described, but other solving methods may be used.

  In the above embodiment, the production plan formulation device 10 includes the display unit 93 and the input unit 95, and the user inputs the figure number data via the input unit 95 and the processing result is displayed on the display unit 93. Explained the case. However, the present invention is not limited to this, and figure number data is input from a user terminal (such as a PC) connected to the production plan formulation device 10, and the processing result of the production plan formulation device 10 is displayed on the display unit of the user terminal. May be displayed. For example, the cloud server 100 connected to a network 80 such as the Internet as shown in FIG. In this case, the cloud server 100 receives the drawing number data input from the user terminal 70, and obtains a solution (manufacturing plan) by executing the processing of FIG. Then, the solution is transmitted from the cloud server 100 to the user terminal 70, and the solution received at the user terminal 70 is displayed. The cloud server 100 may be installed either in Japan or overseas.

  The above processing functions can be realized by a computer. In that case, a program describing the processing contents of the functions that the processing apparatus should have is provided. By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable recording medium (except for a carrier wave).

  When the program is distributed, for example, it is sold in the form of a portable recording medium such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory) on which the program is recorded. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

  The computer that executes the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. Further, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

  The above-described embodiment is an example of a preferred embodiment of the present invention. However, the present invention is not limited to this, and various modifications can be made without departing from the scope of the present invention.

10 Manufacturing Plan Formulating Device 34 Dynamic Optimization Calculation Unit (Second Search Unit)
44 Integer plan optimization calculation unit (first search unit)

Claims (11)

A production plan formulation device for formulating a production plan for multiple types of products,
A first search unit for searching for a combination of products to be set in an apparatus capable of setting a plurality of products simultaneously by integer programming;
A second search unit that searches for a partial combination of the plurality of types of products that can be set in the device by dynamic programming when the first search unit cannot search the combination within a predetermined time. ,
When the search is performed by the second search unit, the first search unit excludes products included in the combination searched by the second search unit and executes the search again. Manufacturing plan development device.   The second search unit analyzes a text for identifying the product to determine a search order of the products, and based on the search order, sets a part of the plurality of types of products that can be set in the device. The manufacturing plan formulation device according to claim 1, wherein the combination is searched by dynamic programming.   The manufacturing plan formulation device according to claim 2, wherein the second search unit determines a search order of the products based on a result of multivariate analysis of the product information.   The second search unit performs a search by dynamic programming when the combination cannot be searched within the predetermined time as a result of the actual search performed by the first search unit. Item 4. The production plan formulation device according to any one of Items 1 to 3.   The said 2nd search part performs a search by a dynamic programming, when the said multiple types of product does not satisfy | fill the conditions which can search the said combination within the said predetermined time. The manufacturing plan formulation device according to any one of the above. A manufacturing plan formulation method for formulating a production plan for multiple types of products,
Search for combinations of products to be set in a device that can set multiple products at the same time by integer programming,
In the process of searching by the integer programming method, when the combination cannot be searched within a predetermined time, the computer searches for a partial combination of the plurality of types of products that can be set in the device by the dynamic programming method. Runs and
When the process of searching by the dynamic programming is executed, the product included in the combination searched by the dynamic programming is excluded, and the process of searching by the integer programming is executed again. Manufacturing plan formulation method.   In the process of searching by the dynamic programming, the text for identifying the product is analyzed to determine the search order of the products, and the plurality of types of products that can be set in the device based on the search order The manufacturing plan formulation method according to claim 6, wherein a part of the combinations is searched by dynamic programming.   The manufacturing plan formulation method according to claim 7, wherein, in the process of searching by the dynamic programming method, a search order of the products is determined based on a result of multivariate analysis of the product information.   In the process of searching by the dynamic programming, if the combination cannot be searched within the predetermined time as a result of actually performing the search by the integer programming, the search is performed by the dynamic programming. The manufacturing plan formulation method according to any one of claims 6 to 8, wherein the manufacturing plan is formulated.   2. The process of searching by the dynamic programming, wherein the plurality of types of products perform a search by a dynamic programming method when the condition for searching for the combination within the predetermined time is not satisfied. The manufacturing plan formulation method as described in any one of 6-8. A manufacturing plan formulation program for formulating a production plan for multiple types of products,
Search for combinations of products to be set in a device that can set multiple products at the same time by integer programming,
In the process of searching by the integer programming method, when the combination cannot be searched within a predetermined time, the computer searches for a partial combination of the plurality of types of products that can be set in the device by the dynamic programming method. To run
When the process of searching by the dynamic programming is executed, the product included in the combination searched by the dynamic programming is excluded, and the process of searching by the integer programming is executed again. A featured manufacturing planning program.

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