Commodity layout planning method and device, equipment and storage medium

Abstract

The invention discloses a commodity layout planning method, device and equipment and a storage medium, relates to the technical field of logistics supply chains, and discloses a commodity layout planning method comprising the following steps: obtaining supply chain data, and generating a feasible performance routing set through the supply chain data; generating a library-crossing route set according to the feasible fulfillment route set; and constructing a mixed integer programming model according to the feasible fulfillment routing set and the library crossing routing set, and outputting a commodity layout scheme through the mixed integer programming model. Through the mode, the scheme can be automatically calculated only by inputting various parameters related to the supply chain during commodity layout planning, and the problem that the cost of the supply chain is increased due to insufficient experience of manual planning is avoided. By solving the mixed integer programming model, a commodity layout scheme with the minimum supply chain network cost is output, and the high efficiency of supply chain operation is ensured.

Description

Technical Field

[0001] The present application relates to the field of logistics supply chain technology, and in particular to commodity layout planning methods, devices, equipment and storage media. Background Art

[0002] In the supply warehousing scenario, due to differences in sales of various commodities in different regions, the upper limit of commodity types managed by each warehouse, the upper limit of inventory storage quantity of each warehouse, and the delivery fulfillment time standards of each commodity in each region are different. Therefore, the commodities produced from the factory need to be differentiated in terms of warehousing based on the above characteristics: deciding which warehouse to store which commodities and the service scope of each warehouse, so as to reduce the cost of cross-regional transfer of commodities and inventory stagnation costs caused by inaccurate stocking.

[0003] Decision makers in enterprises usually make decisions manually based on their business experience. However, manual decision making has a prominent shortcoming. When faced with a complex supply chain network, people are weak in processing global information and find it difficult to make the best global decision. They often fall into the dilemma of making decisions in a single region, which leads to an increase in inventory and transfer costs.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a commodity layout planning method, device, equipment and storage medium, aiming to solve the technical problem that it is difficult for humans to make a globally optimal commodity layout decision.

[0006] To achieve the above objectives, the present application proposes a commodity layout planning method, the method comprising: Acquire supply chain data, and generate a set of feasible fulfillment routes based on the supply chain data; generating a cross-docking route set according to the feasible fulfillment route set; A mixed integer programming model is constructed according to the feasible fulfillment route set and the cross-docking route set, and a commodity layout plan is output through the mixed integer programming model.

[0007] Optionally, the step of generating a set of feasible fulfillment routes through the supply chain data includes: Determine demand point information and demand commodity information according to the supply chain data; A feasible fulfillment route set is generated according to the demand point information, the demand commodity information and preset priority rules.

[0008] Optionally, the step of generating a feasible fulfillment route set according to the demand point information, the demand commodity information and a preset priority rule includes: Determine multiple routing links according to the demand commodity information and the demand point information; Determine routing edge information according to the routing link and preset priority rules; A feasible fulfillment routing set is generated based on the routing link and the routing edge information.

[0009] Optionally, the step of determining routing edge information according to the routing link and a preset priority rule includes: Determine the initial screening edge information of each routing link as the current link according to the preset priority rule; The initially screened edge information is updated according to the edge rollback list and the current routing list to obtain routing edge information.

[0010] Optionally, the step of generating a cross-docking route set according to the feasible fulfillment route set includes: Obtaining cross-docking routing conditions, and determining link constraint conditions according to the cross-docking routing conditions; The feasible fulfillment route set is screened according to the link constraint conditions to obtain a cross-docking route set.

[0011] Optionally, the step of filtering the feasible fulfillment route set by the link constraint condition to obtain the cross-docking route set includes: Determine the delivery time constraint, link combination constraint and warehouse constraint according to the link constraint conditions; The warehouse links in the feasible fulfillment route set are screened according to the delivery time constraint, the link combination constraint and the warehouse constraint to obtain a cross-docking route set.

[0012] Optionally, the step of constructing a mixed integer programming model according to the feasible fulfillment route set and the cross-docking route set includes: Determine model variable information according to the feasible fulfillment route set and the cross-docking route set; Constructing a cost constraint function and an objective function according to the model variable information; A mixed integer programming model is constructed according to the cost constraint function and the objective function.

[0013] In addition, to achieve the above purpose, the present application also proposes a commodity layout planning device, the commodity layout planning device comprising: A normal set building module, used to obtain supply chain data and generate a feasible fulfillment route set through the supply chain data; A cross-docking set building module, used for generating a cross-docking route set according to the feasible fulfillment route set; The layout plan generation module is used to construct a mixed integer programming model according to the feasible fulfillment route set and the cross-docking route set, and output a commodity layout plan through the mixed integer programming model.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a commodity layout planning device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the commodity layout planning method as described above.

[0015] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the commodity layout planning method described above are implemented.

[0016] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the commodity layout planning method as described above.

[0017] One or more technical solutions proposed in this application have at least the following technical effects: The present application obtains supply chain data and generates a feasible fulfillment route set through the supply chain data; generates a cross-docking route set based on the feasible fulfillment route set; constructs a mixed integer programming model based on the feasible fulfillment route set and the cross-docking route set, and outputs a commodity layout plan through the mixed integer programming model. In this way, when planning the commodity layout, it is realized that only various parameters related to the supply chain need to be input to automatically calculate the plan, thus avoiding the increase in supply chain costs caused by lack of experience in manual planning. By solving the mixed integer programming model, the commodity layout plan with the lowest supply chain network cost is output, ensuring the efficiency of supply chain operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0020] Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1A flow chart of the first embodiment of the commodity layout planning method of the present application; Figure 2 A flow chart of the second embodiment of the commodity layout planning method of this application; Figure 3 A flow chart for generating a feasible fulfillment route set provided in an embodiment of a commodity layout planning method of the present application; Figure 4 This is a schematic diagram of the module structure of the commodity layout planning device according to an embodiment of the present application; Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the commodity layout planning method in the embodiment of the present application.

[0022] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0023] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0024] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0025] The main solution of the embodiment of the present application is: by acquiring supply chain data, and generating a set of feasible fulfillment routes through the supply chain data; generating a cross-docking route set based on the feasible fulfillment route set; constructing a mixed integer programming model based on the feasible fulfillment route set and the cross-docking route set, and outputting a commodity layout plan through the mixed integer programming model.

[0026] In this embodiment, for ease of description, the following description is made by taking the identification of the commodity layout planning device as the execution subject.

[0027] In the supply warehousing scenario, due to the differences in sales volume of various commodities in different regions, the upper limit of commodity types managed by each warehouse, the upper limit of inventory storage quantity of each warehouse, and the delivery fulfillment time standards of each commodity in each region are different. Therefore, the commodities produced by the factory need to be differentiated in terms of warehousing based on the above characteristics: deciding which warehouses should store which commodities and the service scope of each warehouse, so as to reduce the cost of cross-regional transfer of commodities and inventory stagnation costs caused by inaccurate stocking.

[0028] Decision makers in enterprises usually make decisions manually based on their business experience. However, manual decision making has a prominent shortcoming. When faced with a complex supply chain network, people are weak in processing global information and find it difficult to make the best global decision. They often fall into the dilemma of making decisions in a single region, which leads to an increase in inventory and transfer costs.

[0029] This application provides a solution, which enables the automatic calculation of the plan by only inputting various parameters related to the supply chain when planning the product layout, thus avoiding the increase in supply chain costs caused by insufficient experience in manual planning. By solving the mixed integer programming model, the product layout plan with the lowest supply chain network cost is output, thus ensuring the efficiency of supply chain operations.

[0030] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device, server, etc. that can realize the above functions.

[0031] The present embodiment and the following embodiments are described below by taking a commodity layout planning device as an example.

[0032] Based on this, the present application embodiment provides a commodity layout planning method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the commodity layout planning method of the present application.

[0033] In this embodiment, the commodity layout planning method includes steps S10 to S30: Step S10, obtaining supply chain data, and generating a feasible fulfillment route set through the supply chain data; It should be noted that the present invention aims to provide enterprises with complex supply chain networks with an efficient and automatic commodity layout planning solution based on current needs and warehouse network structure, solve the decision-making problem of enterprises in planning supply chain commodity warehousing, thereby reducing the overall operating cost of the supply chain and improving the efficiency of supply chain operations.

[0034] It should be understood that the solution of this embodiment includes: Data preprocessing: Based on the existing warehouse network structure data, transportation data, inventory strategy data, product data and demand data, a feasible fulfillment route set is generated for each demand, including normal routes and cross-docking routes.

[0035] Calculate parameters related to each route: transportation cost, timeliness, inventory cost, etc.

[0036] Model solution: Based on the feasible route set, a route-based mixed integer programming model is established: with the goal of minimizing cost, constraints such as timeliness, number of warehouse goods, factory capacity, and transportation resource consumption are established.

[0037] When the data scale is huge, users can use column generation or other methods to control the number of routing variables to achieve good solution results, avoiding problems such as memory overflow and solution timeout that may be caused by directly solving the model.

[0038] Result output: Get the model calculation results and convert them into the optimal product layout plan table to guide enterprises in product warehouse planning.

[0039] It should be noted that various professional terms in the solution of this embodiment include: Fulfillment routing: refers to all the links that goods go through from the factory to the customer; Truckload transportation: refers to the transportation of goods in units of one truckload of goods; Less-than-truckload transport: refers to the cargo consigned on one cargo waybill (a batch) whose weight or volume is not enough to load a truck (i.e., not enough for full truckload transport); LTL level: LTL transportation prices vary according to the quantity (weight or volume) of the waybill; the range of quantities corresponding to different prices is called LTL level; Cross-docking: refers to the operation of goods entering and leaving the warehouse only, without operations such as shelving, storage, and picking; One-time fixed warehouse costs: warehouse costs consisting of warehouse facilities, warehouse decoration, etc., which are paid only once when the warehouse is opened; Warehouse one-time fixed cost threshold: The one-time fixed cost of a warehouse varies depending on the volume of cargo it handles. The volume range corresponding to different one-time fixed costs is called the warehouse one-time fixed cost threshold.

[0040] In specific implementation, supply chain data refers to the data required for collecting planning models, including: transportation data (transportation method, transportation cost, departure interval), warehouse rental data, warehouse fixed cost data, product parameters (volume, weight, selling price, cost), factory capacity data, demand data, address information, warehouse network hierarchy information and procurement strategy information between warehouses.

[0041] It should be noted that after obtaining the supply chain data, analysis of demand points and demand commodities is performed based on the supply chain data to establish a feasible normal fulfillment route set.

[0042] Step S20, generating a cross-docking route set according to the feasible fulfillment route set; It should be understood that after obtaining the feasible fulfillment route set, the feasible fulfillment route set is screened, so as to obtain a cross-docking route set that meets the cross-docking conditions.

[0043] In a feasible implementation manner, in order to generate a cross-docking route set, step S20 includes: A cross-docking routing condition is obtained, and a link constraint condition is determined according to the cross-docking routing condition; and the feasible fulfillment routing set is screened according to the link constraint condition to obtain a cross-docking routing set.

[0044] In a specific implementation, a cross-docking route that meets the cross-docking route conditions is generated based on a known normal route of “demand point i+commodity s”.

[0045] It should be noted that the cross-docking routing condition is essentially to constrain each link and edge of the routing set, that is, the link constraint condition, so as to obtain the cross-docking routing set.

[0046] In a feasible implementation manner, in order to obtain a cross-docking route set by performing link constraints, the feasible fulfillment route set is screened by the link constraints, and the step of obtaining the cross-docking route set includes: The delivery time constraint, the link combination constraint and the warehouse constraint are determined according to the link constraint conditions; the warehouse links in the feasible fulfillment route set are screened according to the delivery time constraint, the link combination constraint and the warehouse constraint to obtain a cross-docking route set.

[0047] It should be noted that the distribution failure constraint refers to the requirement to meet the customer's delivery timeliness requirements when generating cross-docking routes. That is, the total delivery timeliness from the inventory warehouse to the demand point cannot exceed the demand point timeliness constraint. Link combination constraint: the link combination of "non-cross-docking in the lower link and cross-docking in the upper link" is not allowed; warehouse constraint: the upstream warehouse connected to the factory cannot be cross-docking (that is, the factory is not allowed to ship directly to the customer).

[0048] It should be understood that each warehouse link of the normal route can be enumerated to perform cross-docking operations, and check whether its cross-docking route complies with the rules. All cross-docking routes that comply with the rules are saved to obtain the cross-docking route set of "demand point i+commodity s".

[0049] Step S30: construct a mixed integer programming model according to the feasible fulfillment route set and the cross-docking route set, and output a commodity layout plan through the mixed integer programming model.

[0050] In the specific implementation, after obtaining the feasible fulfillment route set and the cross-docking route set, the model is constructed through pre-set constraints and objective functions to obtain a mixed integer programming model, so that the mixed integer programming model can be solved using a commercial solver. After the solution is completed, the model results are read and the solution is output.

[0051] In a feasible implementation, in order to construct a mixed integer programming model, step S30 includes: determining model variable information based on the feasible fulfillment route set and the cross-docking route set; constructing a cost constraint function and an objective function based on the model variable information; and constructing a mixed integer programming model based on the cost constraint function and the objective function.

[0052] It should be noted that the model variable information needs to be determined first, including: The symbol comparison of the model set is shown in Table 1; The symbol table of model parameters is shown in Table 2; The model variable table is shown in Table 3.

[0053] Table 1:

[0054] Table 2 shows the symbols of the model parameters and related descriptions, specifically the symbols of the parameters in the mixed integer programming model. The specific content of Table 2 is as follows.

[0055] Table 2:

[0056] Table 3 includes the symbols of various variables in the mixed integer programming model and related explanations. Among them, the "0-1 variable" and "01 variable" in Table 3 refer to variables whose values ​​can only be 0 or 1. The specific contents of Table 3 are as follows.

[0057] Table 3:

[0058] It should be understood that after determining the model variable information, it is necessary to determine the constraint function and the objective function.

[0059] In the specific implementation, the objective function is:

[0060] In the objective function, the first item represents the total cost of LTL transportation; the second item represents the total cost of full truckload transportation; the third item represents the total cost of express transportation; the fourth item represents the total inventory cost; the fifth item represents the total warehouse rental cost; the sixth item represents the total one-time fixed cost of the warehouse; the seventh and eighth items represent the total warehousing and total outbound costs respectively; the ninth item represents the cost incurred when the variety of warehouse goods does not meet the specified upper and lower limits; the tenth item represents the cost incurred when the demand timeliness achievement quantity does not meet the requirements.

[0061] Constraint 1:

[0062] This constraint states that each demand must have a unique route to fulfill it.

[0063] Constraint 2:

[0064] This constraint means that if edge a is used, then at least one route passing through edge a must be used.

[0065] Constraint 3:

[0066] Among them, M is a sufficiently large positive number. This constraint means that if the route passing through edge a is used, then edge a must be used.

[0067] Constraint 4:

[0068] This constraint means that if a certain outbound edge of warehouse j and commodity s is used, then warehouse j has inbound and outbound operations for the commodity.

[0069] Constraint 5:

[0070] This constraint indicates that if there is an inbound and outbound operation of commodity s in warehouse j, then an outbound edge between warehouse j and commodity s must be used.

[0071] Constraint 6:

[0072] in, Indicates the virtual warehouse corresponding to the physical warehouse r. A virtual warehouse is created for each warehouse. When a route crosses the warehouse, it is considered that the route passes through the virtual warehouse corresponding to this warehouse. This constraint indicates that if there is a warehouse entry and exit operation in warehouse r, the warehouse is used.

[0073] Constraint 7:

[0074] This constraint means that if warehouse r is used, the number of commodity types in warehouse r should exceed the specified lower limit requirement.

[0075] Constraint 8:

[0076] This constraint indicates that the number of commodity types in warehouse r should be lower than the specified upper limit requirement.

[0077] Constraint 9:

[0078] This constraint indicates that the average daily cargo volume should meet the cargo volume requirement corresponding to the time limit tl.

[0079] Constraint 10:

[0080] This constraint states that the factories used cannot exceed their capacity limits for each combination of goods.

[0081] Constraint 11:

[0082] This constraint means that if an edge with LTL as the transport mode is used, one of its levels must be used.

[0083] Constraint 12:

[0084] This constraint indicates that if edge a uses LTL level k, its cargo volume should be greater than the lower limit of this level.

[0085] Constraint 13:

[0086] This constraint indicates that if edge a uses LTL level k, its cargo volume should be less than the upper limit of this level.

[0087] Constraint 14:

[0088] This constraint states that the total quantity of side a using LTL transport is equal to the sum of the quantities on each of its levels.

[0089] Constraint 15:

[0090] This constraint indicates that when edge a using LTL transportation uses level k, there can be cargo volume at this level.

[0091] Constraint 16:

[0092] This constraint indicates that the vehicle capacity used by routes using full truckload transportation should meet the cargo demand.

[0093] Constraint 17:

[0094] This constraint states that if warehouse r is used, then r has a one-time fixed cost threshold.

[0095] Constraint 18:

[0096] If the constrained warehouse is at the one-time fixed cost threshold m, its average daily cargo flow should be greater than the lower limit required by this threshold.

[0097] Constraint 19:

[0098] If the constrained warehouse is at the one-time fixed cost level m, its average daily cargo flow should be greater than the upper limit required by this level.

[0099] This embodiment provides a method for merchandise layout planning, which obtains supply chain data and generates a feasible fulfillment route set through the supply chain data; generates a cross-docking route set based on the feasible fulfillment route set; constructs a mixed integer programming model based on the feasible fulfillment route set and the cross-docking route set, and outputs a merchandise layout plan through the mixed integer programming model. In this way, when planning merchandise layout, it is only necessary to input various parameters related to the supply chain to automatically calculate the plan, thereby avoiding the increase in supply chain costs caused by lack of experience in manual planning. By solving the mixed integer programming model, the merchandise layout plan with the lowest supply chain network cost is output, thereby ensuring the efficiency of supply chain operations.

[0100] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S10 includes steps S101~S102: Step S101, determining demand point information and demand commodity information according to the supply chain data; It should be noted that, at the initial stage of the process, information on demand point i and demand commodity s is obtained.

[0101] Step S102, generating a feasible fulfillment route set according to the demand point information, the demand commodity information and preset priority rules.

[0102] It should be understood that after determining the demand product information and demand point information, the preset priority rules are introduced to generate a feasible fulfillment route set. Among them, the fulfillment route link is initialized to only contain i, and the edges of the fulfillment route path are empty sets; the current link of the update process is demand point i, and then the preset priority rules are introduced.

[0103] In a feasible implementation, in order to obtain a feasible fulfillment route set based on preset priority rules, step S102 includes: determining multiple routing links based on the demand product information and the demand point information; determining routing edge information based on the routing links and preset priority rules; and generating a feasible fulfillment route set based on the routing links and the routing edge information.

[0104] It should be noted that Figure 3 The specific flow chart of this step is as follows: First, multiple routing links, that is, nodes of demand points and factories, are determined based on the demand commodity information and demand point information to obtain the complete route from demand point to factory. Multiple different normal routes can be generated by enumerating warehouses (distribution warehouses) connected to demand points, and then the routing edge information, that is, the connection between links and nodes, is determined to finally obtain a complete routing network.

[0105] In a feasible implementation manner, in order to obtain routing edge information, the step of determining routing edge information according to the routing links and preset priority rules includes: determining the preliminary screening edge information of each routing link when it is the current link according to the preset priority rules; updating the preliminary screening edge information according to the edge rollback list and the current routing list to obtain routing edge information.

[0106] It should be understood that to find the next link of the current link: filter all edges whose end points are the current link, get their end points, and exclude the points included in the rollback list and the current routing list to get the candidate set of the next link. According to the specific priority rules, determine the next link from the set: The preset priority rules include: Priority a: If the current link is a demand point, if there is a next link that meets the timeliness requirements, only all the next links that can meet the timeliness requirements are retained; if there is no next link that meets the timeliness requirements, the next link with the closest distance is retained; Priority b: Filter the next link according to the administrative region priority of "city> province> cross-province". Priority c: Warehouse level relationship priority. If this link is a demand point, it is filtered according to "third-level warehouse> second-level warehouse> first-level warehouse> source of goods"; if this link is a third-level warehouse, it is filtered according to "second-level warehouse> first-level warehouse> source of goods"; if this link is a second-level warehouse, it is filtered according to "first-level warehouse> source of goods"; if this link is a first-level warehouse, the next link candidate set only retains the source of goods. Priority d: If the set obtained by the above priority filtering is not empty, the point closest to this link is filtered from the set as the next link of the route. Fallback: If the candidate set of the next link candidate of the current link is empty, the current link is added to the rollback list and returns to the previous link of the current route. Complete: If the next link is the factory, the complete route from demand point to factory has been obtained, and the search is ended.

[0107] This embodiment determines the demand point information and the demand commodity information according to the supply chain data; generates a feasible fulfillment route set according to the demand point information, the demand commodity information and the preset priority rules. In this way, a cross-docking route set is constructed, so that a mixed integer model can be constructed later, and the model is solved using an efficient column selection idea, which ensures the solution efficiency and the quality of the output solution.

[0108] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the commodity layout planning method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0109] This application also provides a commodity layout planning device, please refer to Figure 4 , the commodity layout planning device comprises: The normal set building module 10 is used to obtain supply chain data and generate a feasible fulfillment route set through the supply chain data.

[0110] The cross-docking set building module 20 is used to generate a cross-docking route set according to the feasible fulfillment route set.

[0111] The layout plan generating module 30 is used to construct a mixed integer programming model according to the feasible fulfillment route set and the cross-docking route set, and output a commodity layout plan through the mixed integer programming model.

[0112] This embodiment obtains supply chain data and generates a feasible fulfillment route set through the supply chain data; generates a cross-docking route set based on the feasible fulfillment route set; constructs a mixed integer programming model based on the feasible fulfillment route set and the cross-docking route set, and outputs a commodity layout plan through the mixed integer programming model. In this way, when planning the commodity layout, it is realized that only various parameters related to the supply chain need to be input to automatically calculate the plan, thereby avoiding the increase in supply chain costs caused by insufficient experience in manual planning. By solving the mixed integer programming model, the commodity layout plan with the minimum supply chain network cost is output, ensuring the efficiency of supply chain operations.

[0113] In one embodiment, the normal set construction module 10 is further used to determine the demand point information and the demand commodity information according to the supply chain data; and generate a feasible fulfillment route set according to the demand point information, the demand commodity information and preset priority rules.

[0114] In one embodiment, the normal set construction module 10 is also used to determine multiple routing links based on the demand product information and the demand point information; determine routing edge information based on the routing links and preset priority rules; and determine and generate a feasible fulfillment routing set based on the routing links and the routing edge information.

[0115] In one embodiment, the normal set construction module 10 is also used to determine the initial screening edge information of each routing link when it is the current link according to the preset priority rule; update the initial screening edge information according to the edge rollback list and the current routing list to obtain the routing edge information.

[0116] In one embodiment, the cross-docking set construction module 20 is further used to obtain cross-docking routing conditions and determine link constraints based on the cross-docking routing conditions; and filter the feasible fulfillment route set according to the link constraints to obtain the cross-docking route set.

[0117] In one embodiment, the cross-docking set construction module 20 is also used to determine the delivery time constraint, the link combination constraint and the warehouse constraint according to the link constraint condition; and to filter the warehouse links in the feasible fulfillment route set according to the delivery time constraint, the link combination constraint and the warehouse constraint to obtain the cross-docking route set.

[0118] In one embodiment, the layout solution generation module 30 is further used to determine model variable information based on the feasible fulfillment route set and the cross-docking route set; construct a cost constraint function and an objective function based on the model variable information; and construct a mixed integer programming model based on the cost constraint function and the objective function.

[0119] The commodity layout planning device provided by the present application adopts the commodity layout planning method in the above embodiment, which can solve the technical problem that it is difficult for humans to make global optimal commodity layout decisions. Compared with the prior art, the beneficial effects of the commodity layout planning device provided by the present application are the same as the beneficial effects of the commodity layout planning method provided by the above embodiment, and the other technical features in the commodity layout planning device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0120] The present application provides a commodity layout planning device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the commodity layout planning method in the above-mentioned embodiment one.

[0121] Reference below Figure 5 , which shows a schematic diagram of the structure of a commodity layout planning device suitable for implementing the embodiment of the present application. The commodity layout planning device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The commodity layout planning device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0122] like Figure 5As shown, the commodity layout planning device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the commodity layout planning device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the commodity layout planning device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a commodity layout planning device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided alternatively.

[0123] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0124] The commodity layout planning device provided by the present application adopts the commodity layout planning method in the above embodiment, which can solve the technical problem that it is difficult for humans to make global optimal commodity layout decisions. Compared with the prior art, the beneficial effects of the commodity layout planning device provided by the present application are the same as the beneficial effects of the commodity layout planning method provided by the above embodiment, and the other technical features in the commodity layout planning device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0125] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0126] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0127] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the commodity layout planning method in the above-mentioned embodiment.

[0128] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0129] The computer-readable storage medium may be included in the commodity layout planning device; or may exist independently without being assembled into the commodity layout planning device.

[0130] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the commodity layout planning device, the commodity layout planning device: obtains supply chain data, and generates a set of feasible fulfillment routes through the supply chain data; generates a cross-docking route set based on the feasible fulfillment route set; constructs a mixed integer programming model based on the feasible fulfillment route set and the cross-docking route set, and outputs a commodity layout plan through the mixed integer programming model.

[0131] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0132] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0133] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0134] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned commodity layout planning method, and can solve the technical problem that it is difficult for humans to make global optimal commodity layout decisions. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the commodity layout planning method provided by the above-mentioned embodiment, and will not be repeated here.

[0135] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned commodity layout planning method when executed by a processor.

[0136] The computer program product provided by this application can solve the technical problem that it is difficult for humans to make global optimal commodity layout decisions. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the commodity layout planning method provided by the above embodiment, which will not be repeated here.

[0137] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A commodity layout planning method, characterized in that: The method includes: Acquire supply chain data, and generate a set of feasible fulfillment routes based on the supply chain data; generating a cross-docking route set according to the feasible fulfillment route set; A mixed integer programming model is constructed according to the feasible fulfillment route set and the cross-docking route set, and a commodity layout plan is output through the mixed integer programming model.

2. The method according to claim 1, characterized in that The step of generating a feasible fulfillment route set through the supply chain data comprises: Determine demand point information and demand commodity information according to the supply chain data; A feasible fulfillment route set is generated according to the demand point information, the demand commodity information and preset priority rules.

3. The method according to claim 2, characterized in that The step of generating a feasible fulfillment route set according to the demand point information, the demand commodity information and the preset priority rule comprises: Determine multiple routing links according to the demand commodity information and the demand point information; Determine routing edge information according to the routing link and preset priority rules; A feasible fulfillment routing set is generated based on the routing link and the routing edge information.

4. The method according to claim 3, characterized in that The step of determining the routing edge information according to the routing link and the preset priority rule comprises: Determine the initial screening edge information of each routing link as the current link according to the preset priority rule; The initially screened edge information is updated according to the edge rollback list and the current routing list to obtain routing edge information.

5. The method according to claim 1, characterized in that The step of generating a cross-docking route set according to the feasible fulfillment route set comprises: Obtaining cross-docking routing conditions, and determining link constraint conditions according to the cross-docking routing conditions; The feasible fulfillment route set is screened according to the link constraint conditions to obtain a cross-docking route set.

6. The method according to claim 5, characterized in that The step of screening the feasible fulfillment route set by the link constraint condition to obtain the cross-docking route set comprises: Determine the delivery time constraint, link combination constraint and warehouse constraint according to the link constraint conditions; The warehouse links in the feasible fulfillment route set are screened according to the delivery time constraint, the link combination constraint and the warehouse constraint to obtain a cross-docking route set.

7. The method according to claim 1, characterized in that The step of constructing a mixed integer programming model according to the feasible fulfillment route set and the cross-docking route set comprises: Determine model variable information according to the feasible fulfillment route set and the cross-docking route set; Constructing a cost constraint function and an objective function according to the model variable information; A mixed integer programming model is constructed according to the cost constraint function and the objective function.

8. A commodity layout planning device, characterized in that: The device comprises: A normal set building module, used to obtain supply chain data and generate a feasible fulfillment route set through the supply chain data; A cross-docking set building module, used for generating a cross-docking route set according to the feasible fulfillment route set; The layout plan generation module is used to construct a mixed integer programming model according to the feasible fulfillment route set and the cross-docking route set, and output a commodity layout plan through the mixed integer programming model.

9. A commodity layout planning device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the commodity layout planning method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the commodity layout planning method according to any one of claims 1 to 7 are implemented.

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