Method for improving article layout, and improvement device

Abstract

To realize increased efficiency in picking operations in a warehouse.SOLUTION: A method for improving article layout comprises: acquiring information regarding a plurality of slots in which articles are arranged; dividing the plurality of slots into a plurality of aisle groups corresponding to a plurality of aisles that can be passed through during picking, based on the information; evaluating the article layout in the plurality of slots based on distances between the plurality of aisle groups; determining whether the evaluation is improved if the positions of articles arranged in the plurality of slots are rearranged based on a predetermined rule, compared to the evaluation before the positions are rearranged; and, if the evaluation is improved, then adopting the rearrangement of the articles.SELECTED DRAWING: Figure 11

Description

[Technical field]

[0001] The present disclosure relates to an article layout improvement method and an improvement device. [Background technology]

[0002] In recent years, the widespread popularity of internet shopping has led to an increase in demand for home delivery, resulting in a labor shortage in warehouses. One of the tasks involved in shipping within a warehouse is "picking," which involves gathering products from within the warehouse that have been instructed to be shipped. As picking is a time-consuming and labor-intensive task, there is a demand to reduce operational costs by making it more efficient.

[0003] Conventionally, in order to improve the efficiency as described above, methods have been considered for optimizing problems from various perspectives such as product placement in a warehouse, movement paths, and generation of pick lists. For example, Non-Patent Document 1 proposes a method using a local search-based algorithm that uses an objective function called PF / PA. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Monika Kofler, “Optimising the storage location assignment problem under dynamic conditions”, [online], May 2015, [Retrieved November 10, 2023], Internet <URL:https: / / www.researchgate.net / publication / 280157450_Optimising_the_storage_location_assignment_problem_under_dynamic_conditions> Summary of the Invention [Problem to be solved by the invention]

[0005] The present disclosure has been devised in consideration of the above-mentioned conventional circumstances, and aims to realize efficient picking work in warehouses. [Means for solving the problem]

[0006] The present disclosure provides a method for improving an item layout, comprising: an acquisition step of acquiring information on a plurality of slots in which items are placed; a grouping step of dividing the plurality of slots into a plurality of aisle groups corresponding to a plurality of aisles that can be passed through during picking based on the information; an evaluation step of evaluating the item layout in the plurality of slots based on the distances between the plurality of aisle groups; and a replacement step of determining whether or not an evaluation by the evaluation step when the positions of the items placed in the plurality of slots are rearranged based on a predetermined rule is improved compared to an evaluation before the positions of the items are rearranged, and adopting a rearrangement of the item arrangement if the evaluation is improved.

[0007] The present disclosure also provides an item layout improvement device having an acquisition unit that acquires information on a plurality of slots in which items are placed, a grouping unit that divides the plurality of slots into a plurality of aisle groups corresponding to a plurality of aisles that can be passed through when picking based on the information, an evaluation unit that evaluates the item layout in the plurality of slots based on the distances between the plurality of aisle groups, and a replacement unit that determines whether or not an evaluation by the evaluation unit when the positions of the items placed in the plurality of slots are rearranged based on a predetermined rule is improved compared to an evaluation before the positions of the items were rearranged, and adopts the rearrangement of the items if the evaluation is improved. Effect of the Invention

[0008] According to the present disclosure, it is possible to realize efficient picking operations in warehouses. [Brief description of the drawings]

[0009] [Figure 1]FIG. 1 is a block diagram showing an example of a hardware configuration of an information processing device that can be used in a system according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a conceptual diagram for explaining a picking operation according to an embodiment of the present invention; [Diagram 3] FIG. 1 is a conceptual diagram for explaining an improvement in a picking operation according to an embodiment of the present invention; [Figure 4] FIG. 1 is a conceptual diagram for explaining a picking operation according to an embodiment of the present invention; [Diagram 5] FIG. 1 is a table showing an example of the configuration of order information and a pick list according to an embodiment of the present invention. [Figure 6] Conceptual diagram to explain the objective function using the conventional PF / PA score [Figure 7] FIG. 1 is a conceptual diagram for explaining a product layout and paths in a warehouse according to an embodiment of the present invention. [Figure 8] FIG. 1 is a conceptual diagram for explaining a product layout and paths in a warehouse according to an embodiment of the present invention. [Figure 9] FIG. 1 is a conceptual diagram for explaining grouping according to an embodiment of the present invention; [Figure 10] FIG. 1 is a conceptual diagram showing an example of grouping according to an embodiment of the present invention; [Figure 11] 1 is a flowchart of an overall process according to an embodiment of the present invention; [Figure 12] 1 is a flowchart of a distance matrix creation process according to an embodiment of the present invention; [Figure 13] 1 is a flowchart of a decision variable creation process according to an embodiment of the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] (Background to this disclosure) In an actual warehouse, some constraints arise in relation to the configuration and operation of the shelves that contain and store the goods to be shipped and the transport vehicles that transport the goods. Therefore, it is required to solve the optimization problem for the picking work by taking such constraints into consideration. For example, if the local search-based algorithm using the PF / PA score shown in Non-Patent Document 1 is directly applied to the optimization problem in a warehouse of a certain size or larger, problems arise in the calculation time and the reduction rate of the moving distance of the picker in the picking work. Therefore, there is a further demand for a method of improving the layout of goods that takes into account the configuration inside the warehouse for the conventional optimization problem.

[0011] Hereinafter, with reference to the drawings as appropriate, each embodiment specifically disclosing the configuration and operation of the article layout improvement method and the improvement device according to the present disclosure will be described in detail. However, more detailed explanation than necessary may be omitted. For example, detailed explanation of already well-known matters and duplicate explanation of substantially the same configuration may be omitted. This is to avoid the following explanation becoming unnecessarily redundant and to facilitate understanding by those skilled in the art. Note that the attached drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0012] <Embodiment 1> [Equipment configuration example] FIG. 1 is a block diagram showing an example of a hardware configuration of an information processing device 10 capable of executing a method for improving an item layout according to a first embodiment of the present invention. The information processing device 10 may be installed as an on-premise device in a warehouse where picking work is performed, and configured as part of a system (hereinafter also referred to as a "warehouse system") that manages the warehouse. Alternatively, the information processing device 10 may be configured as a cloud-based device connected to the warehouse system via a network. In the following description, items to be shipped are described as "products", but this is not intended to limit the targets of improvement of the layout in the warehouse.

[0013] A warehouse system may include, for example, a warehouse management system, a warehouse operations management system, a warehouse control system, an automated warehouse, and a guided vehicle. The various systems and devices included in a warehouse system are configured to be able to communicate with each other via wired / wireless networks. A warehouse management system is a system that manages and controls the logistics within a warehouse, and, for example, manages the inventory of items within the warehouse, as well as the entry and exit (receiving and shipping) and movement of items. A warehouse management system may also be called a Warehouse Management System (WMS).

[0014] A warehouse operations management system is a system that manages and controls work in a warehouse, and is, for example, subordinate to a warehouse management system. A warehouse operations management system may also be called a Warehouse Execution System (WES). For example, a warehouse operations management system comprehensively controls the work content of various work entities in a warehouse and the equipment in the warehouse.

[0015] A warehouse control system manages and controls each of the various pieces of equipment in a warehouse. A warehouse control system is sometimes called a Warehouse Control System (WCS).

[0016] The automated warehouse includes, for example, a plurality of shelves as described below, and a storage case (not shown) is installed in each of a plurality of spaces (hereinafter referred to as "slots") provided on the shelves. One or more products of one type or a plurality of types are stored in one storage case. For ease of explanation, it is assumed here that one storage case provided in a slot stores one or a plurality of products of one type. The automated warehouse is also configured so that products can be moved, stored, and kept in each slot under the control of the warehouse system. The movement of products in the automated warehouse may be configured to be executable by a specified device, or may be achieved by manual work.

[0017] The transport vehicle is operated by a worker (hereinafter also referred to as a "picker") and moves to the position of a slot on a shelf where a desired product (a product to be picked) is stored, and is used when picking the desired product. The configuration of the transport vehicle is not particularly limited. For example, a forklift or the like may be used as the transport vehicle, or a cart on which a collection box (not shown) in which the picked product is stored may be mounted. The transport vehicle is not limited to being driven by a worker, and may be configured to automatically travel along a transport route described later. For example, an Automatic Guided Vehicle (AGV) or an Autonomous Mobile Robot (AMR) may be considered. The picking work may be performed by a human worker, or may be automatically performed by a robot or the like installed on the transport vehicle. For the sake of simplicity, an example of picking using a transport vehicle will be described below, but a configuration may also be used in which a human worker picks products along a transport route described later without using a transport vehicle.

[0018] The information processing device 10 according to the present embodiment includes a processing device 11, a storage device 12, a communication device 13, an input device 14, a display device 15, and an external interface 16. Each part is configured to be able to communicate with each other via an internal interface 17. The processing device 11 may be configured using, for example, a Central Processing Unit (CPU), a Graphical Processing Unit (GPU), a Micro Processing Unit (MPU), a Digital Signal Processor (DSP), or a Field-Programmable Gate Array (FPGA). The processing device 11 realizes various functions, which will be described later, by, for example, referring to various databases (hereinafter, referred to as DB) stored in the storage device 12 or reading out programs. The storage device 12 is a storage unit for storing various data, programs, and the like, and may be configured from, for example, a volatile / non-volatile storage device such as a Random Access Memory (RAM), a Read Only Memory (ROM), or a Hard Disk Drive (HDD).

[0019] The communication device 13 is an interface for communicating with an external device via the network 35. There is no particular limitation on the communication standard that the communication device 13 can support, and it may be wired or wireless. In addition, the communication device 13 may be capable of supporting multiple communication standards. Therefore, the network 35 may be configured by combining networks based on multiple communication standards.

[0020] The input device 14 accepts operations and instructions from users of the warehouse (e.g., a manager or a picker). The input device 14 may be composed of a mouse, a keyboard, a touch panel display, etc. The display device 15 displays various user interfaces to the user. The display device 15 may be composed of a liquid crystal display, a touch panel display, a lamp, etc. The external interface 16 is an interface for communicating with the external system 20. The external system 20 may be communicatively connected via the communication device 13 and a network 35. The external system 20 is not limited to the systems and devices that constitute the warehouse system, but may be other systems or devices.

[0021] [Picking work] FIG. 2 is a conceptual diagram for explaining a picking operation according to the present embodiment. Here, in order to simplify the explanation, an example of a warehouse 300 viewed from above is shown. A plurality of shelves 400 are installed in the warehouse 300, and here, four shelves 400a to 400d are arranged. Each shelf 400 has 2×9 slots 401. Note that, although the height direction is omitted in the example of FIG. 2, an actual shelf may also have a plurality of slots in the height direction.

[0022] In this example, the start position (i.e., the start point of the transport path) and the end position (i.e., the end point of the transport path) of the picking operation by the transport vehicle 200 are specified in advance. A series of picking operations are performed by circulating in front of the slot in which the product to be picked is stored and collecting the product. The transport path that the transport vehicle 200 can pass through is specified along the shelf 400. In other words, the transport path that the transport vehicle 200 can pass when performing the picking operation is composed of one or more aisles, and one aisle is specified along one or two shelves. At this time, as a constraint on the operation of the transport vehicle 200, the transport vehicle 200 can only move in one direction. For example, this is to prevent the transport vehicle 200 from moving backward to pass each other in the same aisle or from causing a collision accident when there are multiple transport vehicles. Also, in the example of FIG. 2, each shelf has two rows of slots, but products cannot be picked across the slots, and products can be picked by positioning in front of the slots in each row.

[0023] Furthermore, there may be empty slots among the multiple slots included in shelf 400. For example, a certain percentage of empty slots may be provided in consideration of when a new type of product arrives or when replenishing or rearranging products.

[0024] In the example of Fig. 2, five products 402a to 402e are to be picked. Product 402a (p3) and product 402b (p1) are stored on shelf 400a. Product 402c (p5) and product 402d (p7) are stored on shelf 400b. Product 402e is stored on shelf 400c. When a picking operation is performed with the five products arranged in this way as the picking targets, a transport route 410 is defined.

[0025] Consider an improvement process for improving the article layout to improve the efficiency of the picking operation, that is, to reduce the conveying distance, for the conveying route 410 shown in Fig. 2. Fig. 3 is a conceptual diagram for explaining an example of the improvement process.

[0026] For example, suppose that product 402e (p8) placed on shelf 400c is moved to shelf 400b. As a result, the transport route for collecting all picking targets changes, and becomes transport route 411. When transport route 410 and transport route 411 are compared, transport route 411 has a shorter distance.

[0027] In this embodiment, multiple orders corresponding to multiple shipping operations are acquired as order information. In each piece of order information, products to be picked are specified. One piece of order information is divided into one or multiple pick lists. An example of division will be described later with reference to FIG. 5. FIG. 4 shows an example of product placement and transport routes corresponding to each of multiple pick lists.

[0028] In a warehouse, products p1 to p9 are arranged as shown in Fig. 4. Furthermore, in picklist A, five products p3, p1, p5, p7, and p8 are specified as items to be picked. In picklist B, three products p3, p1, and p9 are specified as items to be picked. In picklist C, four products p1, p2, p6, and p4 are specified as items to be picked. In this case, products p1 and p3 are duplicated in multiple picklists.

[0029] 4, the transport routes corresponding to pick lists A, B, and C are transport routes 421, 422, and 423. The order of the products specified in pick lists A, B, and C corresponds to the order in which the products are picked.

[0030] FIG. 5 is a diagram showing an example of order information and a pick list according to this embodiment. Order information 500 is generated in response to a shipping request from an orderer of a product. Order information 500 may be generated by any of the systems constituting the warehouse system, or may be acquired from an external system. Order information 500 includes an order ID for uniquely identifying an order, a customer name for uniquely identifying an orderer, a date indicating the date of order, and a product name indicating the item to be ordered (i.e., the item to be picked). Note that the configuration of order information 500 is just an example, and other items may be included.

[0031] In this embodiment, one or more picklists are generated from one piece of order information based on the arrangement of products in a warehouse, predefined picking conditions, etc. A picklist includes a picklist ID for uniquely identifying the picklist, and a product name indicating the product to be picked. Note that the structure of the picklist is just an example, and other items may be included.

[0032] Pick list 510 shows an example of four pick lists generated based on the order ID "order001" of the order information 500 shown in FIG. 5. Fifteen products p01 to p15 are specified in the order information of the order ID "order001". In generating a pick list, first, the products specified in the order information of interest are rearranged based on the product layout in the warehouse. For example, the products may be rearranged in the order of products arranged on the shelf closest to the starting point. Furthermore, the rearranged multiple products are divided according to predefined picking conditions. The picking conditions may be defined based on, for example, the upper limit of the volume, the upper limit of the weight, the urgency, etc. of the products that can be stored in the transport vehicle in one picking operation.

[0033] In the generated picklist 510, picklist ID "Picklist A" specifies four products: p15, p14, p13, and p12. Picklist ID "Picklist B" specifies six products: p11, p10, p09, and p08. Picklist ID "Picklist C" specifies three products: p05, p04, and p03. Picklist ID "Picklist D" specifies two products: p02 and p01. The order of the products specified in picklists A to D corresponds to the order in which they will be picked.

[0034] [Warehouse information] Examples of various information handled in this embodiment (hereinafter collectively referred to as "warehouse information") are shown below. Note that the warehouse information shown below is an example and is not limited to this. The warehouse information according to this embodiment includes slot arrangement information, product storage information, intersection information, entrance information, exit information, product information, picking rule information, etc.

[0035] The slot arrangement information indicates information about slots that constitute shelves in a warehouse. The slot arrangement information includes a slot name for uniquely identifying the slot, the position coordinates (x, y, z) of the slot in the warehouse, an aisle ID for uniquely identifying the aisle to which the slot belongs, a pick route number indicating the order of picking in the aisle to which the shelf to which the slot belongs is located, and a zone ID for uniquely identifying the zone to which the shelf to which the slot belongs (for example, a refrigerated area or a freezer area). In this example, the position coordinates are shown as an example in an absolute coordinate system (three axes: X-axis, Y-axis, and Z-axis) in the warehouse, but are not limited to this. For example, they may be shown in a relative coordinate system for each area in the warehouse.

[0036] The product storage information indicates information about the products stored on the shelf. The product storage information includes a product ID for uniquely identifying the stored product, a storage slot name for uniquely identifying the slot in which the product is stored, and the like.

[0037] The intersection information indicates information about the intersection of the passages defined around multiple shelves in the warehouse. The intersection information includes an intersection ID for uniquely identifying the intersection, intersection coordinates (x, y) indicating the coordinates of the intersection in the warehouse, and intersection details (entrance / exit) indicating the position of the intersection on the transport route.

[0038] The entrance information indicates the coordinates (x, y) of the entrance in the warehouse, i.e., the start point of the transport route. The exit information indicates the coordinates (x, y) of the exit in the warehouse, i.e., the end point of the transport route.

[0039] The product information indicates information related to the characteristics of each product, including the volume and weight of the product.

[0040] The picking rule information indicates conditions related to the picking work of products. The picking rule information is used, for example, when generating a pick list as described above, when determining a transport route, when determining the processing order of each order information, etc. The picking rule information may be defined based on, for example, the maximum load volume of a transport vehicle, the maximum load weight of a transport vehicle, pick list division conditions, etc.

[0041] [Local search based algorithm using PF / PA score] In this embodiment, a method for further improving the item layout is proposed based on the local search-based algorithm using the PF / PA score shown in Non-Patent Document 1. Here, the local search-based algorithm will be briefly described.

[0042] Figure 6 is a conceptual diagram for explaining the optimization of product layout by the method described in Non-Patent Document 1. This is an optimization algorithm based on the policy of arranging products with high order frequency near the entrance and exit, and arranging products with high co-sale rates (probability of being purchased at the same time) close to each other. The symbols in Figure 6 indicate the following: A,B1,B2,C:Product I / O: Entrance / exit PF: Order frequency x distance of product from entrance / exit PA: Concurrent sales rate x distance between products

[0043] PF and PA can be calculated by the following formulas (1) and (2). Then, optimization is performed by searching for a product placement that minimizes the PF / PA score, which is expressed as α·PF+β·PA. Here, α and β are weights. Details of each parameter included in formulas (1) and (2) are described in Non-Patent Document 1, so they will not be repeated here.

[0044]

number

[0045] When calculating the above formulas (1) and (2), the order frequency, the concurrent sales rate, and the distance are calculated in a matrix as shown in the following formulas (3) to (12). Each variable is defined as follows. p:Product s:slot N: Total number of items M: Total number of slots O: Total number of orders F: An N×1 frequency matrix, showing the percentage of shipments of a certain product. A: N×N cross-selling matrix. Shows the proportion of a certain product and a certain product that are placed in the same order (cross-selling rate). D: M × M distance matrix. Shows the distance between two slots. X: N×M decision variable matrix. Elements take values ​​0 or 1. n(p i ,p j ):Product p i and product p j The number of orders that include both

[0046]

number

[0047]

number

[0048]

number

[0049] Here, each row of the decision variable matrix X corresponds to a product p1, p2, . . . and each column corresponds to a slot s1, s2, .

[0050]

number

[0051]

number

[0052] In the decision variable matrix X shown in the above formula (7), “1” indicates the position (slot) of the product. For example, 1 Slot s 2 When changing the product placement, the rows in the decision variable matrix X that correspond to the positions before and after the change are swapped. Also, dist(s k ,s l ) is the position s when moving along the passage k and position s l Therefore, the distance from the position s k and position s l This is different from the straight-line distance.

[0053] In formula (11) for calculating the PF score, items with high shipping frequency are placed in slots closer to the entrance / exit by making the value smaller. In formula (12) for calculating the PA score, items with high concurrent sales rates are placed closer to each other by making the value smaller.

[0054] FIG. 7 is a conceptual diagram for explaining a change in the distance of the conveying path due to a change in the arrangement of the products according to the present embodiment. Here, five aisles 701a to 701e are taken as an example for explanation. Also, it is assumed that the start point of the conveying path is on the upper side of the aisle 701a, and the end point of the conveying path is on the lower side of the aisle 701e. As shown in the upper right of FIG. 7, shelves are arranged on at least one of the actual aisles. Here, for the sake of simplicity, the shelves are omitted, and the products arranged on the shelves on the left and right of the aisle are arranged on the aisle for explanation. By passing through the aisle, it is possible to pick up the products located on the shelves on both sides. In the example in the upper right of FIG. 7, the products to be picked are arranged on both the right shelf and the left shelf, but the same simplified expression may be adopted even when the products to be picked are arranged on only one of the shelves. This is because the products that can be picked up from the aisle are the same whether they are distributed and arranged on the shelves on both sides or only on one shelf.

[0055] In the example arrangement shown at the top of Fig. 7, products 702a and 702b to be picked are arranged in aisle 701c. In the case of the arrangement shown at the top of Fig. 7, by proceeding along conveyance route 703a, the picking work can be performed in the order of product 702b and product 702a.

[0056] In the example arrangement shown at the bottom of Fig. 7, product 702a to be picked is placed in aisle 701c, and product 702b is placed in aisle 701d. In the arrangement shown at the bottom of Fig. 7, by proceeding along conveyance route 703b, the picking work can be performed in the order of product 702a and product 702b.

[0057] In the two layout examples shown in Fig. 7, the conventional optimization algorithm using PF / PA scores gives the lower side a lower score, i.e., it is evaluated as being more optimized. This is because the distance on the conveyance path between product 702a and product 702b in the lower layout is shorter than the distance on the conveyance path between product 702a and product 702b in the upper layout.

[0058] However, when comparing the transport route 703a and the transport route 703b, the total route distance is shorter on the upper side of Fig. 7. This is due to the constraints on the transport of the transport vehicle (the passages are one-way). Therefore, in the case of the arrangement example shown in Fig. 7, it is expected that the conventional optimization algorithm using the PF / PA score will not perform appropriate optimization.

[0059] This embodiment has a configuration for dealing with the phenomenon described in FIG. 7. In the conventional method, the distance between slots is used. In contrast, in this embodiment, the distance between the aisles to which the slots belong is defined, and further improvements are made. More specifically, the units for calculating the distance are specified by grouping each slot by the aisle, and the distance between the aisles is defined by taking into account the transport route through the aisle.

[0060] 8 is a conceptual diagram for explaining grouping according to this embodiment. Here, five aisles are taken as an example for explanation. Here, the aisle length of each aisle is indicated by l, and the distance between the aisles is indicated by w. Product 801a is placed in aisle 1, and product 801b is placed in aisle 5.

[0061] In this embodiment, the distance between the aisles to which the slots belong is used instead of the distance between the slots. For example, the transport route 802a indicates the transport route for picking up the product 801a, and the distance is (l+4w). The transport route 802b indicates the transport route for picking up the products 801a and 801b, and the distance is (3l+4w). These distances are calculated at the time when the transport route is specified. By using such distances per aisle, it is possible to reflect the constraints (characteristics) in an actual warehouse, that is, the cost of the picking work, i.e., the distance value, increases when crossing aisles due to the arrangement of the products.

[0062] 9 and 10 are diagrams for explaining an example of grouping of each slot on a shelf. In FIG. 9, three rows of shelves 903a to 903c are shown, and each shelf is composed of 2×4 slots. In addition, above and below each shelf, passage entrances 901a to 901c and passage entrances 902a to 902c are defined based on layout information such as intersections in the warehouse information. Based on this information, a passage group for each slot is set. In this example, four passage groups are set. As an example, a passage group 905 is set. This corresponds to the passage indicated by the entrance 901c and the exit 902c, and is composed of a slot row 904e of shelf 903b and a slot row 904f of shelf 903c. A passage ID for unique identification is assigned to each passage group.

[0063] Grouping can be defined as the same group when the distance from the entrance to the product to the exit is constant. Therefore, it can be applied to any arrangement where the slots are arranged consecutively in the vertical or horizontal direction.

[0064] Fig. 10 shows another example of grouping. Slots in the same group are represented by the same hatching, etc. In layout 1000, six shelves, each having 2 x 3 slots, are arranged. In this case, eight aisle groups are set. In layout 1010, six shelves, each having 4 x 2 slots, are arranged. In this case, eight aisle groups are set.

[0065] Layout 1020 shows an example of inappropriate grouping. In layout 1020, four aisle groups are set. In this case, the shortest transport route for picking up product A, product B, and product C is transport route 1112. Also, the shortest transport route for picking up product A and product C is transport route 1112. In this case, even though the same aisle group is used, the distance is not uniquely determined. In contrast, by defining it as in layout 1030, it becomes possible to uniquely determine the distance. In layout 1030, eight aisle groups are set. The distances of transport routes 1131 and 1132 are uniquely determined by using different aisle groups. In other words, the distance of one aisle corresponding to one aisle group is fixed.

[0066] When using such grouping, path groups are assigned instead of slots on the horizontal axis shown in the above formula (7). Also, by substituting the number of path groups instead of the number of slots, the number of elements in the matrix is ​​reduced, and the amount of calculation is also reduced.

[0067] [Processing flow] 11 is an overall flowchart of the improvement process of the item layout according to this embodiment. This process flow may be realized, for example, by the processing device 11 of the information processing device 10 reading and executing programs and data stored in the storage device 12 to control each component of the information processing device 10. This process flow may be started when a user of the information processing device 10 instructs the start of the improvement process of the item layout according to this embodiment. Furthermore, the movement of goods within the warehouse may be performed for each predetermined area within the warehouse, or may be performed during a predetermined time period.

[0068] The information processing device 10 acquires order information corresponding to the shipping request (step S1101). The order information here is acquired by a configuration as shown in FIG. 5. The order information may be automatically transmitted from an external system, or may be acquired by the information processing device 10 making an inquiry. The order information will be described as using order information to be shipped in the future. However, this is not limited to this, and in addition to order information to be shipped in the future, order information that has already been processed in the past may be included. For example, past order information may be used when performing statistical processing in the processing described later. In addition, in this process, after acquiring the order information, processing to generate a pick list may be performed as described with reference to FIG. 5. Alternatively, a configuration may be used in which a pick list generated based on the order information is acquired.

[0069] The information processing device 10 acquires predefined warehouse information (step S1102). The warehouse information includes various pieces of information as described above. After this step, the processes of steps S1103 to S1106 are performed. The various processes of steps S1103 to S1106 may be performed simultaneously in parallel or in a predetermined order.

[0070] The information processing device 10 creates a co-sale matrix (step S1103). The co-sale matrix corresponds to the above formula (4). The co-sale matrix indicates the co-sale ratio between two products, and is created from, for example, order information.

[0071] The information processing device 10 creates a distance matrix (step S1104). The distance matrix corresponds to the above formula (8). Details of this processing step will be described with reference to FIG.

[0072] The information processing device 10 creates decision variables (step S1105). Details of this processing step will be described with reference to FIG.

[0073] The information processing device 10 creates a frequency matrix (step S1106). The frequency matrix indicates the shipping frequency of each product, and is created from, for example, order information.

[0074] After the processes of steps S1103 to S1106 are completed, the process of the information processing device 10 proceeds to step S1107. The information processing device 10 randomly rearranges the product arrangement (step S1107). Specifically, the arrangement is rearranged by rearranging the rows of the matrix showing the product arrangement shown in the above formula (7). The rearrangement here corresponds to the rearrangement of products between slots belonging to different aisle groups, not the rearrangement of products between slots belonging to the same aisle group. This is because, in the method according to the present embodiment, when products are rearranged between slots belonging to the same aisle group, no change occurs in the PF / PA cost. Note that, although the rearrangement is random in this example, the rearrangement may be performed based on a predetermined rule. For example, the neighborhood search here may use a known Swap neighborhood.

[0075] The information processing device 10 calculates the PF / FA scores of the layout rearranged in step S1107 (step S1108). The calculation method here is based on the technique of Non-Patent Document 1 and is performed using the above formulas (11) and (12). In this embodiment, in order to reduce the calculation load corresponding to a huge variety of products, some of the calculation results of the evaluation values ​​are reused. For example, when the product arrangement is rearranged, only two rows change. In other words, the calculation results other than the changed rows are the same as before the rearrangement, so the previous results can be reused. In this embodiment, such reuse reduces the cost of the improvement process and shortens the calculation time.

[0076] For example, when swapping product positions, the first and second rows of the determinant in the following equation (13) are swapped. In this case, the third row and below remain unchanged, so these values ​​can be used as they were before the swap. Therefore, the calculations for the third row and below can be omitted.

[0077]

number

[0078] The information processing device 10 compares the PF / PA score calculated immediately before in step S1108 with the PF / PA score calculated previously, and determines whether the value calculated immediately before has improved (step S1109). Improvement here means that the PF / PA score has become smaller. If the PF / PA score has improved (step S1109: YES), the information processing device 10 proceeds to step S1110. On the other hand, if the PF / PA score has not improved (step S1109: NO), the information processing device 10 proceeds to step S1111.

[0079] With the improvement in the PF / PA score, the information processing device 10 adopts a corresponding product replacement (step S1110). Specifically, a decision variable corresponding to the arrangement of the products after the replacement is updated. At this time, it may further determine in which slot of the aisle group the products after the replacement will be arranged. For example, the products may be arranged in an empty slot in the aisle group to which they belong, or a specific slot may be determined based on a predetermined condition. Then, the process of the information processing device 10 proceeds to step S1112.

[0080] The information processing device 10 probabilistically adopts the replacement of the product (step S1111). The probability here may be predefined or may be changed according to the processing result of the past order information. Therefore, if the PF / PA score has not improved, it is determined whether or not to adopt the replacement of the product probabilistically. If the replacement is adopted, it may be further determined in which slot of the aisle group the replaced product will be placed. For example, it may be placed in an empty slot of the aisle group to which it belongs, or a specific slot may be determined based on a predetermined condition. Note that the reason why the replacement of the product may be adopted in step S1111 even if the PF / PA score has not improved is that in the local search approach, the solution obtained in the subsequent iterations may be improved by intentionally adopting a solution that does not improve the score. Therefore, if the purpose is to obtain a result earlier than a more improved result, the replacement of the product may not be adopted at all in step S1111. In this case, only the replacement that improves the PF / PA score is adopted, so that the speed at which the PF / PA score converges to a local minimum value is increased. Then, the processing of the information processing device 10 proceeds to step S1112.

[0081] The information processing device 10 determines whether the processes of steps S1107 to S1111 have been repeated a predetermined number of times. The predetermined number of times may be predefined. If the processes have been repeated the predetermined number of times (step S1112: YES), the information processing device 10 finalizes the current product layout and ends this processing flow. On the other hand, if the processes have not been repeated the predetermined number of times (step S1112: NO), the information processing device 10 returns to step S1107 and repeats the processes.

[0082] The processes in steps S1107 to S1111 are a local search approach, and use Simulated Annealing (SA).

[0083] (Create distance matrix) FIG. 12 is a flowchart of the distance matrix creation process according to this embodiment, which corresponds to step S1104 in FIG.

[0084] The information processing device 10 performs grouping of slots based on the warehouse information as described with reference to Fig. 9 and Fig. 10 (step S1201). For the grouping here, slot arrangement information, entrance information, exit information, intersection information, etc. acquired as the warehouse information are used.

[0085] The information processing device 10 calculates the distance between the passages for each passage group obtained in step S1201 (step S1202). The distance between the passages can be calculated by using the above formulas (9) and (10) and defining it as shown in FIG.

[0086] The information processing device 10 creates a distance matrix based on the distances between the passages obtained in step S1202 (step S1203). The distance matrix is ​​configured as shown in the above formula (8). Then, this processing flow ends.

[0087] (Create decision variables) FIG. 13 is a flowchart of the process of generating decision variables according to this embodiment, which corresponds to step S1105 in FIG.

[0088] The information processing device 10 allocates products to each slot based on grouping (step S1301). The allocation here is performed based on product storage information in the warehouse information. Note that it is assumed that grouping of each slot has been completed in the process of step S1201 in FIG. 12 before the process here is executed.

[0089] Based on the result of the allocation in the process of step S1301, the information processing device 10 creates corresponding decision variables. Specifically, the decision variable matrix X shown in the above formula (7) is generated. Then, this processing flow ends.

[0090] [Reduction of calculation amount] In the optimization algorithm of Non-Patent Document 1, the amount of calculation required to calculate the PF / PA score is defined by the following equation (13).

[0091]

number

[0092] On the other hand, the method according to this embodiment reduces the amount of calculations compared to the method according to Non-Patent Document 1 by reducing the order and using differential calculations. In the warehouse according to this embodiment, products placed on the same aisle do not affect the conveying distance regardless of which slot they are placed in. In this embodiment, the order is reduced by grouping slots and performing calculations as aisle groups. In this case, the amount of calculations is defined by the following equation (15).

[0093]

number

[0094] Furthermore, in the process of step S1107 in Fig. 11, as explained using formula (13), the difference calculation is performed by omitting the calculation of the parts that do not change before and after the rearrangement of the products. In this case, the amount of calculation is defined by the following formula (16).

[0095]

number

[0096] When comparing the amount of calculation for formula (14) and the amount of calculation for formula (16), although the difference in the amount of calculation varies depending on the warehouse configuration, the amount of calculation for formula (16) by the method according to the present embodiment is smaller. In other words, it is possible to reduce the calculation cost compared to the conventional method.

[0097] As described above, in the method for improving an item layout according to the present embodiment, information on a plurality of slots in which items are arranged is acquired, and based on the information, the plurality of slots are divided into a plurality of passage groups corresponding to a plurality of passages through which items can be passed during picking, and an evaluation of the item layout in the plurality of slots is performed based on the distance between the plurality of passage groups, and it is determined whether or not the evaluation of the item layout in the case where the positions of the items arranged in the plurality of slots are rearranged based on a predetermined rule is improved compared to the evaluation before the rearrangement of the items, and if the evaluation is improved, rearrangement of the item layout is adopted. With this configuration, it is possible to improve the item layout in order to improve the efficiency of picking work in a warehouse. In addition, it is possible to reduce the calculation cost for the improvement.

[0098] In addition, in the method for improving an item layout according to the present embodiment, the predetermined rule is a rule for switching items between slots belonging to different aisle groups. The predetermined rule is also a rule for randomly selecting different aisle groups. The predetermined rule is also a rule for not switching items between slots belonging to the same aisle group. This configuration makes it possible to omit calculations related to switching between products belonging to the same aisle group.

[0099] In addition, in the method for improving the layout of items according to the present embodiment, if the evaluation after the position of the items is swapped is not improved compared to the evaluation before the swap, swapping is probabilistically adopted. With this configuration, even if no improvement is obtained at a certain point in time in the local search approach, it is possible to reflect the property that the solution obtained in the subsequent iterations is further improved.

[0100] In addition, in the method for improving an item layout according to the present embodiment, the items are grouped so that the distance of one aisle corresponding to one aisle group is uniquely determined. With this configuration, the distance of the aisle corresponding to the aisle group can be uniquely specified, and it becomes possible to improve the item layout by taking into consideration, for example, the operational constraints of the transport vehicle at the warehouse site.

[0101] In addition, in the method for improving an item layout according to the present embodiment, slots at positions where picking is possible when passing through one aisle are grouped into an aisle group corresponding to the one aisle. With this configuration, it is possible to calculate distances by treating multiple slots as one group, and it is possible to improve the item layout while reducing calculation costs and taking into account constraints in the warehouse.

[0102] Furthermore, in the method for improving an item layout according to the present embodiment, an item layout in a plurality of slots is evaluated based on the distance between a plurality of aisle groups, the positions of the items arranged in the plurality of slots are rearranged and evaluated, and the positions of the items are rearranged based on the evaluation of the item layout after the positions of the items are rearranged, and this is repeated. According to this configuration, by repeatedly performing an evaluation based on the distance between the aisle groups, it is possible to improve the item layout in consideration of on-site constraints in the warehouse.

[0103] (Other variations) In this embodiment, since a local search approach is adopted, a truly optimal result is not necessarily obtained from all product layouts. Also, if the score is improved by replacing the products, the layout is at least improved compared to before the replacement, so it is not necessarily necessary to repeat the process until a locally optimal solution is obtained. In other words, the method according to this embodiment may be a method for improving the layout, and is not necessarily an optimization method. In other words, the term "optimization" in this specification is intended to include the fact that it may be the search for an optimal solution at a certain point in time, or the search for a relatively improved solution under certain conditions.

[0104] In addition, in this embodiment, the timing of the actual product replacement after the decision to replace the products may be arbitrary. For example, the products already in the slots may not be replaced, and only newly received products may be replaced, or the products in the slots may be replaced as needed. In the latter case, the effect of the product replacement may not be immediate, but as the warehouse entry and exit operations progress, the results of the improvement process according to this embodiment will eventually be reflected in the warehouse layout.

[0105] In addition, the product layout that is the basis for improvement in this embodiment may be a product layout arranged in a real warehouse, or a virtual product layout. When a virtual product layout is used, the processing according to this embodiment may be performed for purposes such as simulation when the layout of a real warehouse is first determined.

[0106] In addition, in this embodiment, the layout improvement method for a warehouse that handles products has been described, but the target of layout improvement does not have to be limited to products. The idea of ​​this embodiment can also be applied to warehouses that handle various items such as prototypes that are not subject to commercial distribution, materials, and parts.

[0107] In the present embodiment, the description has been given assuming that products belonging to the same aisle group are not swapped. However, the configuration may be such that products belonging to the same aisle group are swapped. Although this swapping does not lead to an improvement in the layout from the viewpoint of the aisle group, it may lead to an improvement in the layout from another viewpoint, for example, in that picking efficiency is improved when products of the same height are placed on shelves of similar height.

[0108] In addition, in the present invention, a program or application for realizing the functions of one or more of the above-mentioned embodiments can be supplied to a system or device via a network or a storage medium, etc., and one or more processors in a computer of the system or device can read and execute the program, thereby making it possible to realize the present invention.

[0109] Moreover, it may be realized by a circuit that realizes one or more functions (for example, an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA)).

[0110] In the present embodiment, the terms "first" and "second" are used to distinguish from other elements for convenience. Therefore, these terms should not be interpreted as being limited to specific elements, but may be appropriately interpreted according to changes in components, etc.

[0111] Although various embodiments have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art can conceive of various modifications, corrections, substitutions, additions, deletions, and equivalents within the scope of the claims, and it is understood that these also belong to the technical scope of the present disclosure. In addition, the components in the various embodiments described above may be arbitrarily combined within the scope of the invention.

[0112] (Additional Note) The above-described embodiments disclose the following techniques. (Technology 1) An acquisition step of acquiring information on a plurality of slots in which items are placed; a grouping step of dividing the slots into a plurality of passage groups corresponding to a plurality of passages through which items can be picked based on the information; an evaluation step of evaluating an article layout in the plurality of slots based on distances between the plurality of passage groups; a replacement process for determining whether or not the evaluation by the evaluation process is improved compared to the evaluation before the replacement of the positions of the objects when the positions of the objects arranged in the plurality of slots are replaced based on a predetermined rule, and adopting the replacement of the positions of the objects when the evaluation is improved; The method for improving an article layout comprises:

[0113] (Technology 2) The method for improving an article layout according to Technology 1, wherein the predetermined rule is a rule for switching articles between slots belonging to different passage groups.

[0114] (Technology 3) The method for improving an article layout according to Technology 2, wherein the predetermined rule is a rule for randomly selecting the different aisle groups.

[0115] (Technology 4) The method for improving an article layout according to Technology 2, wherein the predetermined rule is a rule that articles are not swapped between slots belonging to the same passage group.

[0116] (Technology 5) The method for improving an article layout according to any one of Technology 2 to Technology 4, wherein the replacement step probabilistically adopts the replacement when an evaluation after the position of the article is replaced is not improved compared to an evaluation before the position of the article is replaced.

[0117] (Technology 6) The method for improving an article layout according to any one of Techniques 1 to 5, wherein in the grouping step, grouping is performed so that a distance of one passage corresponding to one passage group is uniquely determined.

[0118] (Technology 7) The method for improving an article layout according to any one of Technology 1 to Technology 5, wherein in the grouping step, slots at positions where picking is possible when passing through one aisle are grouped into an aisle group corresponding to the one aisle.

[0119] (Technology 8) The replacing step includes evaluating an article layout in the plurality of slots based on distances between the plurality of passage groups; performing the evaluation by swapping the positions of the articles disposed in the plurality of slots; repeating the step of shuffling the positions of the objects based on an evaluation of the object layout after the shuffling of the positions of the objects; A method for improving an article layout according to any one of Technology 1 to Technology 7.

[0120] (Technology 9) an acquisition unit that acquires information on a plurality of slots in which items are placed; a grouping unit that divides the slots into a plurality of passage groups corresponding to a plurality of passages through which items can be picked based on the information; an evaluation unit that evaluates an article layout in the plurality of slots based on distances between the plurality of passage groups; a replacement unit that determines whether or not an evaluation by the evaluation unit will be improved compared to an evaluation before the replacement of the positions of the objects when the positions of the objects arranged in the plurality of slots are replaced based on a predetermined rule, and adopts the replacement of the positions of the objects when the evaluation is improved; The article layout improvement device has the following features. [Industrial Applicability]

[0121] The present disclosure is useful as an improvement method and an improvement device for improving item layout in picking operations in a warehouse. [Explanation of symbols]

[0122] 10...Information processing device 11... Processing equipment 12...Storage device 13...Communication equipment 14...Input device 15...Display device 16...External interface 20…External system 35…Network 200…Transport vehicle 300…Warehouse 400…Shelf 401...Slots

Claims

1. An acquisition step of acquiring information on a plurality of slots in which items are placed; a grouping step of dividing the slots into a plurality of passage groups corresponding to a plurality of passages through which items can be picked based on the information; an evaluation step of evaluating an article layout in the plurality of slots based on distances between the plurality of passage groups; a replacement process for determining whether or not an evaluation by the evaluation process when the positions of the articles arranged in the plurality of slots are rearranged based on a predetermined rule will improve compared to an evaluation before the positions of the articles are rearranged, and adopting the rearrangement of the articles when the evaluation improves; The method for improving an article layout comprises:

2. 2. The method for improving an article layout according to claim 1, wherein the predetermined rule is a rule for switching articles between slots belonging to different aisle groups.

3. The method for improving an article layout according to claim 2 , wherein the predetermined rule is a rule for randomly selecting the different aisle groups.

4. 3. The method for improving an article layout according to claim 2, wherein the predetermined rule is a rule that articles are not swapped between slots belonging to the same aisle group.

5. 3. The method for improving an article layout according to claim 2, wherein the replacement step probabilistically adopts the replacement when an evaluation after the positions of the articles are replaced is not improved compared to an evaluation before the positions of the articles are replaced.

6. 2. The method for improving an article layout according to claim 1, wherein in the grouping step, grouping is performed such that a distance of one passage corresponding to one passage group is uniquely determined.

7. 2. The method for improving an article layout according to claim 1, wherein in the grouping step, slots at positions where picking is possible when passing through one aisle are grouped into an aisle group corresponding to the one aisle.

8. The replacing step includes evaluating an article layout in the plurality of slots based on distances between the plurality of passage groups; performing the evaluation by swapping the positions of the articles disposed in the plurality of slots; repeating the step of shuffling the positions of the objects based on an evaluation of the object layout after the shuffling of the positions of the objects; The method for improving an article layout according to claim 1 .

9. an acquisition unit that acquires information on a plurality of slots in which items are placed; a grouping unit that divides the slots into a plurality of passage groups corresponding to a plurality of passages through which items can be picked based on the information; an evaluation unit that evaluates an article layout in the plurality of slots based on distances between the plurality of passage groups; a replacement unit that determines whether an evaluation by the evaluation unit when the positions of the objects arranged in the plurality of slots are rearranged based on a predetermined rule will be improved compared to an evaluation before the positions of the objects are rearranged, and adopts the rearrangement of the objects when the evaluation is improved; The article layout improvement device has the following features.

Images