Information processing device, information processing method, information processing program, and information processing system

Abstract

To provide a quantitative method for storing goods and a technology that can improve operational efficiency. [Solution] An information processing device according to an embodiment includes an acquisition unit that acquires an order list, a generation unit that assigns a sequence number to each product and order included in the order list, links the product sequence numbers of the products required for the order to the order sequence numbers, derives combinations of order sequence numbers and product sequence numbers by solving a minimization problem with a predetermined equation as an objective function that is set so that combinations of order sequence numbers and product sequence numbers linked to order sequence numbers are symmetrical, and generates a storage instruction based on the derived combination, and an output unit that outputs a storage instruction.

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an information processing device, an information processing method, an information processing program, and an information processing system. [Background technology]

[0002] In a logistics center using automated guided vehicles (AGVs) to transport shelves, the items listed in each order are stored on individual shelves. The number of shelves typically amounts to several hundred, depending on the scale of the system. These shelves are transported by automated guided vehicles to picking stations according to the order. At the picking stations, the items listed in the order are picked from the shelves and placed in trays assigned to each order. The method of picking items from shelves containing multiple types of products into trays assigned to multiple orders is called multi-picking. In multi-picking, the number of calls for an automated guided vehicle is determined by the order list arrangement and the order in which the shelves are transported to which picking stations. The order list arrangement and the quality of the picking station assignments determine the number of automated guided vehicles required, operational efficiency, and picking efficiency.

[0003] If a plan were made to simply assign the provided order list to each picking station, select the orders according to the order list's order sequence, and pick the items listed in each order in the order listed, the shelf on which each item is stored would have to be carried to the picking station for each item, which would be extremely inefficient. As such, the order list's order sequence has a significant impact on operational efficiency, and the order list's sequence is optimally rearranged based on how the items are stored on each shelf. In other words, operational efficiency varies greatly depending on how the items are placed on each shelf.

[0004] Conventionally, how to place products on each shelf has been determined by a methodology based on the experience of multi-picking by human workers. In addition, for additional stocking, the stocking location is determined each time based on the availability of shelf space and product volume, etc. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 7065693 Summary of the Invention [Problem to be solved by the invention]

[0006] Conventional methods are not quantitative methods that guarantee appropriateness. As a result, it is difficult to guarantee improved operational efficiency in response to environmental changes such as changes in the type or quantity of target products or changes in overall handling volume. Furthermore, fluctuations in operational efficiency can cause the warehouse's processing speed to become unstable.

[0007] The present invention has been made in light of the above-mentioned circumstances, and its object is to provide a quantitative method for storing products and to provide technology that can improve operational efficiency. [Means for solving the problem]

[0008] The information processing device according to the embodiment includes an acquisition unit that acquires an order list, a generation unit that assigns a sequence number to each of the products and orders included in the order list, links the product sequence numbers of the products required for the orders to the order sequence numbers, derives combinations of the order sequence numbers and the product sequence numbers by solving a minimization problem in which a predetermined equation set so that the combinations of the order sequence numbers and the product sequence numbers linked to the order sequence numbers are symmetrical as an objective function, and generates a warehousing instruction based on the derived combination, and an output unit that outputs the warehousing instruction. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a conceptual diagram illustrating an example of a logistics system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of a layout in a warehouse according to one embodiment. [Figure 3] FIG. 3 is a flowchart illustrating an example of a warehousing planning method using a WES, according to one embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of an order list obtained from a WMS according to one embodiment. [Figure 5] FIG. 5 is a flowchart illustrating the process of step ST105 in more detail. [Figure 6] FIG. 6 is a diagram showing an example of a scatter diagram of (i, j) where i is the order number and j is the product number, according to one embodiment. [Figure 7] FIG. 7 is a diagram showing hit rates calculated based on various conditions according to one embodiment. [Figure 8] FIG. 8 is a diagram illustrating a comparison of the hit rate calculated by a conventional method for 30 days with the hit rate calculated by the method described in this embodiment, according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an information processing device, an information processing method, an information processing program, and an information processing system will be described in detail with reference to the drawings. In the following embodiments, parts with the same numbers perform the same operations, and redundant description will be omitted. For example, when there are multiple identical or similar elements, a common symbol may be used to describe each element without distinguishing between them, or a subnumber may be used in addition to the common symbol to describe each element with distinction between them.

[0011] In the following description, the term "A" or "B" means at least one of A or B, and the term "A," "B," or "C" means at least one of A, B, or C. Furthermore, the term "A" and "B" also means at least one of A and B, and the term "A," "B," and "C" means at least one of A, B, and C.

[0012] [Embodiment] (composition) FIG. 1 is a conceptual diagram illustrating an example of a logistics system according to an embodiment. As shown in FIG. 1, the warehouse system S includes a warehouse management system (WMS) 1 and a warehouse processing system 2.

[0013] The warehouse processing system 2 is an example of a product processing system, and includes a warehouse execution system (WES) 30, an automated guided vehicle control system (WCS) 40, an automated guided vehicle 50, and an inventory management system 60.

[0014] The WMS1 can be configured with one or more computers, i.e., processors, memories, interfaces, etc. The processors are CPUs (central processing units), MPUs (micro processing units), DSPs (digital signal processors), etc. The WMS1 receives order lists from the upper server and sends them to the WES30.

[0015] The order list includes information such as the date and time of receipt, the type and quantity of each product required, and the weight and dimensions of the product.

[0016] WES 30 (server) is an example of an information processing device and can be configured with one or more general-purpose computers. WES 30 includes processor 301, memory 302, and interface 303. Processor 301 is a CPU, MPU, DSP, or the like. Memory 302 stores operating programs for processor 301, etc. Interface 303 communicates with WMS 1, automated guided vehicle control system 40, inventory management system 60, etc.

[0017] The processor 301 of the WES 30 includes an acquisition unit 3011, a generation unit 3012, and an output unit 3013. The processor 301 executes a program stored in the memory 302 to realize the functions of each unit.

[0018] For example, the interface 303 receives an order list from WMS1. The acquisition unit 3011 acquires the order list. The generation unit 3012 generates a storage instruction from the order list. The output unit 3013 outputs the generated storage instruction. The interface 303 transmits the storage instruction to the automated guided vehicle control system 40 and the inventory management system 60. The interface 303 also receives a storage processing result from the automated guided vehicle control system 40 and transmits the result to WMS1. The processor 301 updates the inventory management database of the inventory management system 60 according to the storage processing result.

[0019] The automated guided vehicle control system 40 can be configured with one or more general-purpose computers. The automated guided vehicle control system 40 includes a processor 401, a memory 402, and an interface 403. The processor 401 is a CPU, MPU, DSP, or the like. The memory 402 stores the operating program of the processor 401, etc. The interface 403 communicates with the WES 30 and the automated guided vehicle 50. The processor 401 realizes each function by executing the program stored in the memory 402. The processor 401 controls the automated guided vehicle 50 based on a storage instruction sent from the WES 30.

[0020] The automated guided vehicle 50 can be configured with one or more general-purpose computers and includes a processor, memory, an interface, etc. The processor is a CPU, MPU, DSP, etc. The memory stores the processor's operating program, etc. The interface communicates with the automated guided vehicle control system 40. The processor realizes each function by executing the program stored in the memory.

[0021] The automated guided vehicle 50 may be any robot capable of transporting shelves, such as an AGV or an AMR (Autonomous Mobile Robot). The processor transports the shelves 70 storing products to a picking station based on control instructions from the automated guided vehicle control system 40. For example, the automated guided vehicle 50 may be equipped with a camera, analyze images captured by the camera, and move the shelves horizontally along the warehouse floor based on the analysis results. The automated guided vehicle 50 may also travel using the results of reading position identification information affixed to the warehouse floor.

[0022] The inventory control system 60 can be configured with one or more general-purpose computers and includes a processor, memory, and interface. The processor is a CPU, MPU, DSP, or the like. The memory stores an inventory control database, etc. The interface communicates with the WES 30, etc.

[0023] The inventory management database includes map management information, equipment management information, and product management information. The map management information includes warehouse map data (three-dimensional coordinate data), location identification information associated with the map data, and storage location identification information associated with the map data. The equipment management information includes shelf identification information assigned to shelves and container identification information assigned to containers and the like stored on the shelves. The product management information includes product identification information assigned to products. Furthermore, the shelf identification information and container identification information are associated with the map data or storage location identification information, and the positions of each shelf and each container are managed. Furthermore, the product identification information of a specific product is associated with the shelf identification information and container identification information where the specific product is stored, and the storage location of the specific product is managed.

[0024] As described above, the interface 303 receives the warehousing processing result from the automated guided vehicle control system 40. The processor 301 updates the inventory management database based on the warehousing processing result, and the interface 303 transmits the updated inventory management database to the inventory management system 60. The inventory management system 60 stores the updated inventory management database. For example, the warehousing processing result including information such as on which shelf 70 a specific product is stored in accordance with the warehousing processing is received, and the processor 301 reflects the movement result in the inventory management database.

[0025] For example, position identification information that can be read by an automated guided vehicle 50 or the like is attached to the floor of the warehouse. Readable shelf identification information, container identification information, and product identification information are attached to shelves, containers, and products, respectively. For example, each piece of identification information is an optically readable two-dimensional code such as a QR code (registered trademark).

[0026] FIG. 2 is a diagram illustrating an example of a layout in a warehouse according to one embodiment. As shown in Fig. 2, the warehouse includes a shelf inventory area 7 and a picking station area 8. The shelf inventory area 7 is an area for storing shelves 70, and the picking station area 8 includes one or more picking stations 80 and a shelf waiting area 90 arranged adjacent to the picking stations 80.

[0027] The shelves 70 are arranged in the shelf inventory area 7. The shelves 70 are shelves for storing products. For example, the shelves 70 are upright on four support pillars. The height below the shelves 70 (height from the floor to the bottom of the shelf) is higher than the height of the automated guided vehicle 50. This allows the automated guided vehicle 50 to slip under the shelves 70. After slipping under the shelves, the automated guided vehicle 50 uses a pusher to lift the shelves 70 so that the tips of the support pillars are a few centimeters above the floor, and travels with the shelves 70 lifted. In this way, the automated guided vehicle 50 transports the shelves 70.

[0028] The picking station 80 receives the shelves 70 transported by the automated guided vehicles 50. A worker or a picking robot at the picking station 80 picks up an item from the received shelves 70.

[0029] For example, a display is installed in the picking station 80, and the number of items to be picked is displayed on the display. A worker or a picking robot at the picking station 80 stores the required items in a tray on the shelf 70.

[0030] The shelf standby area 90 is an area where the shelves 70 transported by the automatic guided vehicles 50 wait, and is provided adjacent to each picking station 80.

[0031] (operation) FIG. 3 is a flowchart illustrating an example of a warehousing planning method using WES2, according to one embodiment. The operation of this flowchart is realized by processor 301 of WES 30 reading and executing a program stored in memory 302. This flowchart begins when WMS 1 obtains an order list and transmits it to WES 30.

[0032] In step ST101, the acquisition unit 3011 acquires an order list. The acquisition unit 3011 acquires the order list transmitted from the WMS1 via the interface 303. In one embodiment, the order list is a list generated based on a past order list. Alternatively, the order list is a list to be used for future inventory. When generated based on a past order list, the order list may be generated using a general method such as machine learning. Therefore, a detailed description thereof will be omitted here.

[0033] FIG. 4 is a diagram illustrating an example of an order list obtained from WMS1 according to one embodiment. Each row in FIG. 4 corresponds to one order. Furthermore, each order includes the date and time of receipt, slip number, JIS code (denoted as JIS_CD in FIG. 4), product code (denoted as product CD in FIG. 4), quantity, box capacity, box weight, etc. In addition to the above information, an order may also include information about the product, such as product dimensions such as the product's length, width, and depth. Products are shipped in batches of a certain number of slip numbers as shown in FIG. 4. The product code indicates the product number, and several types of products are stored together on the same shelf 70. As shown in FIG. 4, multiple products may be ordered using the same slip number.

[0034] In step ST102, the generation unit 3012 assigns numbers to the products included in the target order list. The generation unit 3012 extracts the types of products included in the order list and sequentially assigns product numbers 1 to n to the extracted products. For example, the generation unit 3012 assigns product numbers 1 to n so that a product number assigned to one product does not overlap with a product number assigned to another product. Here, n represents the total number of product types extracted from the order list.

[0035] In step ST103, the generation unit 3012 assigns sequence numbers to the orders in the target order list. The generation unit 3012 sequentially assigns order sequence numbers from 1 to m to each order in the acquired order list. For example, the generation unit 3012 assigns order sequence numbers from 1 to m so that the order sequence number assigned to one order does not overlap with the order sequence numbers assigned to other orders. Here, m represents the total number of orders included in the order list.

[0036] In step ST104, the generation unit 3012 associates the order sequence number with the product sequence number. For example, the generation unit 3012 acquires the product number of the product required for the order, and associates the order sequence number with the acquired product sequence number. For example, for the i-th order, the required product sequence number j i Here, i is an integer equal to or less than n, i.e., 1≦i≦n, and j i represents the product sequence number of the product included in the i-th order.

[0037] In step ST105, the generation unit 3012 derives the optimal product sequence and order sequence. For example, the generation unit 3012 derives the combination of order sequence numbers and product sequence numbers by solving a minimization problem in which the objective function is a predetermined equation set so that the combinations of order sequence numbers and product sequence numbers linked to the order sequence numbers are symmetrical.

[0038] FIG. 5 is a flowchart illustrating the process of step ST105 in more detail. In step ST201, the generation unit 3012 swaps the product sequence numbers assigned to the products. For example, the generation unit 3012 swaps the product sequence number assigned to a certain product with the product sequence number assigned to another product. Note that the order indicating the arrangement of the products is not changed.

[0039] In step ST202, the generation unit 3012 swaps the order sequence numbers assigned to the orders. For example, the generation unit 3012 swaps the order sequence number assigned to one order with the order sequence number assigned to another order. Note that the order indicating the sequence of the orders is not changed.

[0040] In step ST203, the generation unit 3012 swaps the product sequence numbers of the products linked to the order. For example, the generation unit 3012 swaps the product sequence number assigned to one of the products linked to a certain order with the product sequence numbers assigned to other products linked to the order. Note that the order of the products linked to the order is not changed.

[0041] In step ST204, the generation unit 3012 calculates the value of the following formula (1): That is, the generation unit 3012 calculates the value of formula (1), which is a predetermined formula set so that the combinations of the order sequence numbers and the product sequence numbers linked to the order sequence numbers are symmetrical.

[0042]

number

[0043] Here, I represents the total number of order sequence numbers, and J i represents the product sequence number of the product included in the i-th order. j is an arbitrary positive integer less than or equal to J (or m), and J i Refers to the jth product in the

[0044] In step ST205, the generation unit 3012 determines whether the value of formula (1) is minimum. If it is determined that the value of formula (1) is minimum, the process proceeds to step ST206. On the other hand, if it is determined that the value of formula (1) is not minimum, the process returns to step ST201.

[0045] By repeating the processes of steps ST201 to ST205, the generation unit 3012 derives a combination of order sequence numbers and product sequence numbers that results in a minimum or local minimum value for the value of equation (1). That is, the generation unit 3012 derives a combination of order sequence numbers and product sequence numbers linked to the order sequence numbers by solving the minimization problem of equation (1), which is the objective function. Note that any common method can be used to solve the minimization problem of equation (1), and detailed explanation will be omitted here.

[0046] In step ST206, the generation unit 3012 stores in the memory 302 the combination of the order sequence number and the product sequence number when formula (1) is minimized. The generation unit 3012 may also store in the memory 302 the combination of the product and the product sequence number, and the combination of the order and the order sequence number.

[0047] Returning to FIG. 3 , in step ST106, the generation unit 3012 allocates combinations to be stored on shelves 70 in the order in which the products are arranged. The generation unit 3012 determines which products should be allocated to which shelves 70 in accordance with the derived product sequence numbers. For example, the generation unit 3012 groups the products in accordance with the derived product sequence numbers of the combinations, and allocates the grouped products to shelves 70. In other words, the generation unit 3012 allocates product sequence numbers 1 to n to shelves 70.

[0048] The generation unit 3012 then generates information about the grouped products and the allocated shelves 70 as storage instructions. The output unit 3013 outputs the storage instruction to the automated guided vehicle control system 40 via the interface 303. The processor 401 of the automated guided vehicle control system 40 controls the automated guided vehicle 50 to transport the shelves 70 to the picking station 80 based on the storage instruction. Then, at the picking station 80, a worker or a picking robot stores the products on the shelves 70 in accordance with the storage instruction. The processor 401 then controls the automated guided vehicle 50 to return the shelves 70 with the products stored thereon to the shelf inventory area 7.

[0049] Furthermore, the generation unit 3012 may allocate grouped products to multiple shelves 70 based on the order list. In other words, there may be multiple shelves 70 storing the same product. For example, if the same product is frequently used in multiple orders, storing the product on multiple shelves 70 enables the orders to be processed quickly.

[0050] Alternatively, the generation unit 3012 may group the products so that some of the products overlap. As described above, if the same product is frequently used in multiple orders, storing the product on multiple shelves 70 enables the orders to be processed quickly.

[0051] Furthermore, the generation unit 3012 may group products so that they fit on the shelves 70, further based on the box capacity and box weight included in the order list. Alternatively, the generation unit 3012 may group products based on the quantity of products included in the order list and the number of picking stations 80 in the warehouse. For example, if there are a large number of picking stations 80, there will be a large number of shelves 70 that can be processed at one time. Therefore, the generation unit 3012 takes these factors into consideration when grouping products.

[0052] FIG. 6 is a diagram showing an example of a scatter diagram of (i, j) where i is the order number and j is the product number, according to one embodiment. The x-axis of Fig. 6 represents the order sequence number i, and the y-axis represents the product sequence number j. The diagram on the left of Fig. 6 is a scatter plot in the case where the order sequence number i remains the number initially assigned to a given order, and the product sequence number j is randomly assigned to a given product. The diagram on the right of Fig. 6 is a scatter plot of the order sequence number i and the product sequence number j when the method of this embodiment described above is used. In other words, the diagram on the right of Fig. 6 is a scatter plot of (i, j) when rearranged to minimize the value of equation (1).

[0053] As shown on the left side of Figure 6, the product sequence number j is uniformly distributed with respect to the order sequence number i. In other words, it shows that the order sequence number i is assigned to a given order, and the product sequence number j is randomly assigned to the product. On the other hand, as shown on the right side of Figure 6, when the method of this embodiment is used, the product sequence number j is assigned to a smaller number than the order sequence number i, meaning that the numbers are assigned symmetrically.

[0054] FIG. 7 is a diagram illustrating hit rates calculated based on various conditions according to one embodiment. 7, the horizontal axis represents the hit rate, and the vertical axis represents the frequency at which the hit rate is achieved. Here, the hit rate is a value indicating the number of products that can be picked from one shelf 70.

[0055] Figure 7 shows the following conditions: Condition 1: No inventory reordering or order reordering (Figure 7 (1)), Condition 2: No inventory reordering, but order reordering (Figure 7 (2)), Condition 3: Reordering of inventory and orders (Figure 7 (3)), and Condition 4: Reordering of inventory, but no order reordering (Figure 7 (4)). Inventory reordering refers to whether or not product reordering is performed, and order reordering refers to whether or not order reordering is performed. As Figure 7 shows, condition 3, i.e., reordering both products and orders, has the highest hit rate.

[0056] FIG. 8 is a diagram illustrating a comparison of the hit rate calculated by a conventional method for 30 days with the hit rate calculated by the method described in this embodiment, according to one embodiment. Figure 8(a) shows the hit rate calculated by the conventional method for 30 days and the hit rate calculated by the method described in this embodiment. Figure 8(b) is a graph showing the hit rate calculated by the conventional method for 30 days and the hit rate calculated by the method described in this embodiment. The horizontal axis of Figure 8(b) represents days, and the vertical axis represents the hit rate.

[0057] As shown in FIG. 8, the hit rate calculated by the method described in this embodiment is higher than the hit rate calculated by the conventional method. For example, the hit rate calculated by this embodiment is approximately 1.8 times higher than the hit rate calculated by the conventional method. The improved hit rate improves the throughput in the warehouse processing system 2. Therefore, for example, if the current level of throughput is sufficient, the number of automatic guided vehicles 50 can be reduced.

[0058] (Effects of the embodiment) According to the embodiment described above, the WES 30 determines how to arrange products to be stored on the shelves 70 based on the order list. In other words, by using a quantitative method for storing products, the processing speed of the warehouse system S can be stabilized without causing major changes even if there are environmental changes such as changes in the type and quantity of products and changes in the overall handling volume. This can improve the operational efficiency of the entire warehouse system S.

[0059] [Other embodiments] In the present embodiment, an example has been described in which the WES 30 determines on which shelf 70 the product should be stored, but this is not limiting. For example, the processor of the WMS 10 may execute this process.

[0060] The program according to this embodiment may be transferred in a state where it is stored in an electronic device (computer) such as the WES 30, or may be transferred in a state where it is not stored in an electronic device. In the latter case, the program may be transferred via a network, or may be transferred in a state where it is stored in a storage medium. The storage medium is a non-transitory, tangible medium. The storage medium is a medium that can be read by a computer such as the WES 30 (computer-readable medium). The storage medium may be in any form, such as an optical disk (e.g., a CD-ROM), a magnetic disk, or a semiconductor memory (e.g., a memory card), as long as it is capable of storing a program and is readable by a computer.

[0061] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0062] S...Warehouse system 1. Warehouse management system 2. Warehouse processing system 30...Warehouse operation system 301...Processor 3011…Acquisition Department 3012...Generation section 3013...Output section 302...Memory 303...Interface 40...Automated guided vehicle control system 401...Processor 402...Memory 403...Interface 50...Automated guided vehicle 60...Inventory control system 7...Shelf inventory area 70…Shelf 8. Picking station area 80...Picking station 90…Shelf standby area

Claims

1. an acquisition unit for acquiring an order list; a generation unit that assigns a sequence number to each of the products and orders included in the order list, links the product sequence numbers required for the orders to the order sequence numbers, derives combinations of the order sequence numbers and the product sequence numbers by solving a minimization problem in which a predetermined equation set so that combinations of the order sequence numbers and the product sequence numbers linked to the order sequence numbers are symmetrical is used as an objective function, and generates a warehousing instruction based on the derived combination; an output unit that outputs the storage instruction; An information processing device comprising:

2. The predetermined formula is expressed by the following formula: [Equation 1] I represents the total number of the order sequence numbers, and J ｉ represents the order of the product included in the order with the i-th order sequence number, where i is any positive integer equal to or less than I, j is any positive integer equal to or less than J, and J ｉ represents the j-th product sequence number in The information processing device according to claim 1 .

3. the generation unit rearranges the product sequence numbers assigned to the products, rearranges the order sequence numbers assigned to the orders, rearranges the product sequence numbers of the products linked to the orders of the order sequence numbers, and derives a combination of the order sequence numbers and the product sequence numbers that minimizes the value of the formula using the rearranged order sequence numbers and the product sequence numbers; The information processing device according to claim 2 .

4. the generation unit groups the products based on the derived combination, allocates a shelf in a warehouse to each of the grouped products, and generates, as the warehousing instruction, information about the grouped products and information about the allocated shelf. The information processing device according to claim 1 .

5. the generation unit allocates the grouped products to a plurality of shelves based on the order list. The information processing device according to claim 4 .

6. the generation unit groups the products so that some of the products overlap. The information processing device according to claim 4 .

7. the generation unit groups the products so that they fit on the shelf, further based on box volumes and box weights of the products included in the order list. The information processing device according to claim 4 .

8. the generation unit groups the products based on the quantity of the products included in the order list and the number of picking stations in the warehouse. The information processing device according to claim 4 .

9. The order list is a list generated based on past order lists. The information processing device according to claim 1 .

10. The order list is a list to be used for future shipments. The information processing device according to claim 1 .

11. An information processing method executed by a processor of an information processing device, Obtaining an order list; assigning a sequence number to each of the items and orders included in said order list; Linking the product sequence number of the product number required for the order with the order sequence number; deriving a combination of the order sequence number and the product sequence number by solving a minimization problem in which a predetermined equation set so that the combination of the order sequence number and the product sequence number linked to the order sequence number is symmetrical is used as an objective function; generating a warehousing instruction based on the derived combination; outputting the warehousing instruction; An information processing method comprising:

12. An information processing program comprising instructions to be executed by a processor of an information processing device, the instructions comprising: Obtaining an order list; assigning a sequence number to each of the items and orders included in said order list; Linking the product sequence number of the product required for the order with the order sequence number; deriving a combination of the order number and the product number by solving a minimization problem in which a predetermined equation set so that combinations of the order sequence number and the product sequence number linked to the order sequence number are symmetrical is used as an objective function; generating a warehousing instruction based on the derived combination; outputting the warehousing instruction; An information processing program comprising:

13. Warehouse operation system, an automated guided vehicle control system connected to the warehouse operation system; The warehouse operation system comprises: an acquisition unit for acquiring an order list; a generation unit that assigns a sequence number to each of the products and orders included in the order list, links the product sequence numbers of the products required for the orders with order sequence numbers, derives combinations of the order sequence numbers and the product sequence numbers by solving a minimization problem in which a predetermined equation set so that combinations of the order sequence numbers and the product sequence numbers linked to the order sequence numbers are symmetrical is used as an objective function, and generates a warehousing instruction based on the derived combination; an output unit that outputs the storage instruction; The automated guided vehicle control system comprises: an interface for receiving the warehousing instruction; a processor that controls an automated guided vehicle in a warehouse based on the storing instruction to transport a shelf arranged in a shelf inventory area to a picking station, and after the product is stored on the shelf, controls the automated guided vehicle to transport the shelf to the shelf inventory area; An information processing system comprising:

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