Warehouse distribution method and device, equipment, storage medium and program product

Abstract

The invention discloses a warehouse allocation method, device and equipment, a storage medium and a program product, and relates to the technical field of logistics warehouse management, and the warehouse allocation method comprises the steps: receiving a warehouse allocation request; according to the warehouse allocation request, a departure order set to be allocated to warehouses is obtained, and the departure order set comprises a plurality of departure orders; and based on a mixed integer programming algorithm, according to preset warehouse configuration information, the warehouse allocation request and a plurality of departure orders, warehouse allocation is carried out, and a departure order warehouse allocation result is obtained. According to the invention, departure order warehouse distribution based on the mixed integer programming algorithm is realized, the problem of low logistics efficiency of an existing warehouse distribution method is solved, and the logistics transportation efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of logistics warehousing management, and in particular to a warehouse allocation method, device, equipment, storage medium and program product. Background Art

[0002] In the manufacturing industry, multiple warehouses are often used to store produced goods. There may be overlaps in the commodity collections of different warehouses. At this time, it is necessary to decide on the pick-up warehouse for the dispatch order. There may be only one pick-up warehouse for a dispatch order, or there may be multiple ones.

[0003] However, the existing warehouse allocation method mainly uses manual experience rules to make single dispatch and pickup decisions in the actual operation of dispatching and picking up goods. When there are multiple pickup warehouses, it will increase the driver's pickup time and affect the logistics transportation efficiency.

[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 warehouse allocation method, device, equipment, storage medium and program product, aiming to solve the technical problem of low logistics efficiency of existing warehouse allocation methods.

[0006] To achieve the above objectives, the present application proposes a warehouse allocation method, which includes: Receive warehouse allocation requests; According to the cargo warehouse allocation request, a set of dispatch orders to be allocated to the cargo warehouse is obtained, wherein the set of dispatch orders includes a plurality of dispatch orders; Based on a mixed integer programming algorithm, warehouse allocation is performed according to preset warehouse configuration information, the warehouse allocation request and a number of dispatch orders to obtain a dispatch order warehouse allocation result.

[0007] In one embodiment, the step of performing warehouse allocation based on the mixed integer programming algorithm according to the preset warehouse configuration information, the warehouse allocation request and a number of dispatch orders to obtain the dispatch order warehouse allocation result includes: Generate an objective function and constraints based on the cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders; A model is constructed based on the objective function and constraint conditions to obtain a warehouse allocation model; Solving the warehouse allocation model by using a preset integer programming model solver to obtain a model allocation result; According to the allocation result of the model, the dispatch order warehouse allocation result is obtained.

[0008] In one embodiment, the step of generating an objective function and constraints according to the cargo warehouse configuration information, the cargo warehouse allocation request and a plurality of vehicle dispatch orders comprises: Determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders; Determining an optimization target according to the warehouse allocation request; Based on the allocation decision variables and the optimization goal, an objective function and constraints are generated.

[0009] In one embodiment, the warehouse configuration information includes a set of pickup warehouses and inventory details, an upper limit on warehouse capacity, and one or more of the distances between warehouses; the dispatch order includes a set of commodity details; and the optimization goal includes one or more of the minimum total number of pickup warehouses and the shortest total distances between pickup warehouses.

[0010] In one embodiment, the step of determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a plurality of vehicle dispatch orders comprises: If the warehouse allocation request is to consider the warehouse capacity limit, then determine the allocation decision variables according to the set of available warehouses and inventory details, the warehouse capacity limit and the commodity details set; If the warehouse allocation request is to consider the distance to the pickup warehouse, then determine the allocation decision variables according to the set of available pickup warehouses and inventory details, the distance between warehouses and the set of commodity details; If the warehouse allocation request takes into account the warehouse capacity limit and the distance to the pickup warehouse, the allocation decision variables are determined based on the set of available pickup warehouses and inventory details, the warehouse capacity limit, the distance between warehouses and the set of commodity details.

[0011] In one embodiment, the step of obtaining the dispatch order warehouse allocation result according to the model allocation result includes: Rounding the model allocation result to obtain a rounded model allocation result; According to the warehouse inventory corresponding to the dispatch order set, the allocation quantity of the rounded model allocation result is verified and corrected to obtain the dispatch order warehouse allocation result.

[0012] In addition, to achieve the above-mentioned purpose, the present application also proposes a cargo warehouse allocation device, the cargo warehouse allocation device comprising: A request receiving module, used for receiving a warehouse allocation request; A dispatch order acquisition module, used to acquire a dispatch order set to be allocated to the cargo warehouse according to the cargo warehouse allocation request, wherein the dispatch order set includes a plurality of dispatch orders; The cargo warehouse allocation module is used to perform cargo warehouse allocation based on a mixed integer programming algorithm according to preset cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders, and obtain a dispatch order cargo warehouse allocation result.

[0013] In addition, to achieve the above-mentioned purpose, the present application also proposes a warehouse allocation 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 warehouse allocation method described above.

[0014] 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 the processor, the steps of the warehouse allocation method described above are implemented.

[0015] 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, the steps of the warehouse allocation method described above are implemented.

[0016] The present application provides a warehouse allocation method, which first receives a warehouse allocation request as the starting point of the entire allocation process and triggers subsequent allocation operations; then, according to the warehouse allocation request, obtains all the dispatch orders that need to allocate warehouses to integrate the necessary data required for warehouse allocation; finally, using a mixed integer programming algorithm, the warehouse allocation problem of the dispatch order is modeled as an optimization problem, and warehouse allocation is performed to obtain the dispatch order warehouse allocation result, thereby achieving efficient and reasonable warehouse allocation. The dispatch order warehouse allocation based on the mixed integer programming algorithm is realized, which solves the problem of low logistics efficiency of the existing warehouse allocation method and improves the logistics transportation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] 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.

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 A schematic diagram of a flow chart of a first embodiment of the warehouse allocation method of the present application; Figure 2 A schematic diagram of a flow chart of a mixed integer programming model for constructing the first embodiment of the warehouse allocation method of the present application; Figure 3 A schematic diagram of the flow of model solving and result conversion provided in the first embodiment of the warehouse allocation method of the present application; Figure 4This is a schematic diagram of the module structure of the cargo warehouse allocation device according to an embodiment of the present application; Figure 5 It is a schematic diagram of the equipment structure of the hardware operating environment involved in the warehouse allocation method in the embodiment of the present application.

[0020] 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

[0021] 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.

[0022] 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.

[0023] The main solution of the embodiment of the present application is: receiving a warehouse allocation request; according to the warehouse allocation request, obtaining a set of dispatch orders to be allocated to the warehouse, wherein the set of dispatch orders includes several dispatch orders; based on a mixed integer programming algorithm, performing warehouse allocation according to preset warehouse configuration information, the warehouse allocation request and several dispatch orders, and obtaining a dispatch order warehouse allocation result.

[0024] In most scenarios of logistics and transportation, the starting point of the transportation task is a single source. In this scenario, the dispatch order corresponds to only one pickup warehouse, so there is no need to decide which warehouse to pick up the goods. However, in the manufacturing scenario, multiple warehouses are often used to store the produced goods. There may be overlaps in the cargo collections of different warehouses. At this time, it is necessary to decide the pickup warehouse for the dispatch order. There may be only one pickup warehouse for a dispatch order, or there may be multiple pickup warehouses. When there are multiple pickup warehouses, it will increase the driver's pickup time, poor pickup experience and increased pickup costs. Therefore, it is hoped to minimize the phenomenon of picking up goods from multiple warehouses.

[0025] Since in practice, single decisions are mainly made manually based on experience, this rule is a greedy rule that pursues local optimality. It will allocate pickup warehouses to each dispatch order in turn, and try to make the number of pickup warehouses as small as possible during the allocation process. However, this method is difficult to obtain the optimal solution in multi-warehouse allocation scenarios.

[0026] This application first receives a warehouse allocation request as the starting point of the entire allocation process, triggering subsequent allocation operations; then, according to the warehouse allocation request, obtains all the dispatch orders that need to be allocated warehouses to integrate the necessary data required for warehouse allocation; finally, using the mixed integer programming algorithm, the warehouse allocation problem of the dispatch order is modeled as an optimization problem, and the warehouse allocation is performed to obtain the dispatch order warehouse allocation result, thereby achieving efficient and reasonable warehouse allocation. The dispatch order warehouse allocation based on the mixed integer programming algorithm is realized, which solves the problem of low logistics efficiency of the existing warehouse allocation method and improves the efficiency of logistics transportation.

[0027] 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, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a warehouse distribution device, etc. The following takes the warehouse distribution device as an example to illustrate this embodiment and the following embodiments.

[0028] Based on this, the embodiment of the present application provides a warehouse allocation method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the warehouse allocation method of the present application.

[0029] In this embodiment, the cargo warehouse allocation method includes steps S10 to S30: Step S10, receiving a warehouse allocation request; It should be noted that the warehouse allocation request is used to trigger the allocation process and provide the basic data required for allocation, including basic information of the allocation task, such as the quantity, type, priority, destination, allocation requirements, etc. of the goods.

[0030] It can be understood that receiving a warehouse allocation request from the outside, starting the warehouse allocation process, triggering subsequent allocation operations, and providing necessary input data for subsequent steps.

[0031] Step S20, according to the cargo warehouse allocation request, obtaining a set of dispatch orders to be allocated to the cargo warehouse, wherein the set of dispatch orders includes a plurality of dispatch orders; It should be noted that the dispatch order set contains multiple dispatch orders, each of which records detailed information of the goods (such as the quantity of goods, destination, etc.).

[0032] It is understandable that in order to collect all the dispatch orders that need to be allocated to a warehouse and provide a data basis for the subsequent allocation algorithm, all dispatch orders to be allocated and processed are extracted and integrated from the database or logistics system according to the received warehouse allocation request.

[0033] Step S30, based on a mixed integer programming algorithm, warehouse allocation is performed according to preset warehouse configuration information, the warehouse allocation request and a number of dispatch orders to obtain a dispatch order warehouse allocation result.

[0034] It should be noted that the Mixed Integer Programming (MIP) algorithm is a mathematical optimization method for solving complex resource allocation problems. It can achieve efficient warehouse allocation by optimizing the allocation problem. Warehouse configuration information refers to the configuration information related to the warehouse, which can include information such as commodity inventory and warehouse location, as constraints and judgment basis in the mixed integer programming algorithm. The dispatch order warehouse allocation result contains information such as the warehouse and the number of commodities corresponding to each dispatch order, which can be used as the basis for actual dispatch and pickup, and provide a specific implementation guide for logistics operations.

[0035] It can be understood that by using the mixed integer programming algorithm, the warehouse allocation problem is modeled as an optimization problem, and the optimal allocation solution is solved to meet the actual needs and realistic limitations of warehouse allocation. At the same time, it can significantly improve warehouse utilization, reduce operating costs, and improve the overall efficiency of the logistics system.

[0036] In a feasible implementation manner, the step of performing warehouse allocation based on the mixed integer programming algorithm according to the preset warehouse configuration information, the warehouse allocation request and a number of dispatch orders to obtain the dispatch order warehouse allocation result includes: Step S301, generating an objective function and constraint conditions according to the cargo warehouse configuration information, cargo warehouse allocation request and a number of vehicle dispatch orders; It should be noted that the objective function refers to the goal of defining the optimization, such as minimizing warehouse utilization, maximizing cargo distribution efficiency, minimizing transportation costs, etc., which is used to guide the direction of optimization and ensure that the allocation plan meets the optimization goal. Constraints refer to the actual needs that the warehouse allocation plan needs to meet, such as warehouse capacity restrictions, cargo storage conditions, departure time windows, etc., which are used to limit the feasibility of the allocation plan and ensure that the plan meets actual needs.

[0037] It can be understood that according to the warehouse configuration information, warehouse allocation request and dispatch order set, the key parameters are extracted, and combined with the actual optimization goals (single objective or multiple objectives), the objective function and constraints of the mathematical model are constructed, and a clear mathematical expression is provided for the objective function and constraints, which serves as the basis for subsequent model construction.

[0038] Step S302, constructing a model based on the objective function and constraint conditions to obtain a warehouse allocation model; It should be noted that the warehouse allocation model refers to a complete mathematical model that integrates the objective function and constraints based on the principle of mixed integer programming algorithm, providing an operational mathematical form for the solver to ensure that the problem can be solved.

[0039] It can be understood that in order to transform the complex warehouse allocation problem into a solvable mathematical optimization model, the objective function and constraints are integrated into a mixed integer programming model for warehouse allocation of dispatch orders to ensure that the model can accurately reflect the constraints and objectives of the actual problem.

[0040] Step S303, solving the warehouse allocation model by a preset integer programming model solver to obtain a model allocation result; It should be noted that the integer programming model solver is used to solve the mixed integer programming model, such as CPLEX, Gurobi and other commercial solvers. You can choose a suitable solver according to the scale and complexity of the problem to ensure the solution efficiency.

[0041] It can be understood that in order to obtain the optimal solution or approximate optimal solution to the warehouse allocation optimization problem, a pre-set integer programming model solver is used to solve the constructed warehouse allocation model to find the optimal or approximate optimal warehouse allocation solution as the model allocation result.

[0042] Step S304, obtaining the dispatch order warehouse allocation result according to the model allocation result.

[0043] It should be noted that the model allocation result refers to the mathematical result output by the solver when solving the model, which is used to provide an optimized allocation plan. The dispatch order warehouse allocation result refers to the specific warehouse allocation plan, such as the dispatch order number, warehouse number, warehouse location, etc., to provide guidance for actual operations.

[0044] It can be understood that in order to convert the results of the mathematical model into a guiding plan for actual operations, the mathematical results output by the model (such as variable values) are converted into specific warehouse allocation information (such as dispatch order number, warehouse number), thereby converting the model allocation results obtained by the solver into a specific warehouse allocation plan.

[0045] In this implementation, first, by generating the objective function and constraints, the optimization direction and rules are clarified; then, these rules are integrated into a complete mathematical model to provide an operational form for the solver; then, the model is solved using an efficient solver to find the optimal or approximately optimal allocation plan; finally, the solution result is converted into a specific allocation plan and its feasibility is verified. It can not only quickly respond to warehouse allocation requests, but also provide the optimal allocation plan in complex logistics scenarios, which can significantly improve warehouse utilization, reduce operating costs, and improve the overall efficiency of the logistics system.

[0046] In a feasible implementation manner, the step of generating an objective function and constraint conditions according to the cargo warehouse configuration information, the cargo warehouse allocation request and a plurality of vehicle dispatch orders includes: Step S3011, determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a number of vehicle dispatch orders; It should be noted that the allocation decision variable represents the specific parameters of the allocation plan, such as "whether dispatch order i is allocated to warehouse j", which is the core of the optimization model, used to represent the specific form of the allocation plan, and is the object of the optimization algorithm operation.

[0047] It can be understood that in order to clarify the variables that need to be optimized in the model and provide a basis for the subsequent construction of objective functions and constraints, the decision variables that need to be optimized are identified based on the warehouse configuration information, warehouse allocation requests and dispatch orders.

[0048] Step S3012, determining an optimization target according to the cargo warehouse allocation request; It should be noted that the optimization goal defines the direction of optimization, such as minimizing cost, maximizing efficiency, etc. The optimization goal corresponds to the "objective function" of the model and determines the optimization direction of the model. The optimization goal can be a single goal (such as minimizing cost) or multiple goals (such as balancing efficiency and cost).

[0049] It is understandable that in order to clarify the direction of optimization and ensure that the model can solve the key requirements of actual problems, the core requirements of the warehouse allocation task are analyzed according to the warehouse allocation request and the optimization goal is determined.

[0050] Step S3013, generating an objective function and constraint conditions based on the allocation decision variables and the optimization target.

[0051] It should be noted that the objective function refers to the mathematical function expression of the quantitative optimization goal, which is used to guide the direction of optimization and ensure that the goal pursued by the model is consistent with the actual needs. Constraints refer to the rules that limit the feasibility of the allocation plan, such as warehouse capacity restrictions, cargo storage conditions, etc., which can ensure the feasibility of the optimization results and avoid generating unrealistic allocation plans.

[0052] It can be understood that the actual problem is converted into the form of a mathematical model so that it can be solved by the optimization algorithm. Based on the determined decision variables and optimization objectives, the objective function and constraints of the mathematical model are constructed, so that the objective function is used to quantify the optimization goal and the constraints are used to ensure the feasibility of the allocation plan.

[0053] In this implementation, firstly, by determining the allocation decision variables, the key parameters that need to be optimized in the model are clarified; then, according to the warehouse allocation request, the optimization goal is determined to indicate the optimization direction for the model; finally, based on the decision variables and the optimization goal, the objective function and constraints are generated, and the actual problem is converted into a mathematical model, which can not only quickly build the optimization model, but also provide flexible and reliable solutions in complex logistics scenarios.

[0054] In a feasible implementation, the warehouse configuration information includes a set of pickup warehouses and inventory details, an upper limit on warehouse capacity, and one or more of the distances between warehouses; the dispatch order includes a set of commodity details; and the optimization goal includes one or more of the minimum total number of pickup warehouses and the shortest total distances between pickup warehouses.

[0055] It should be noted that the warehouse collection and inventory details clearly state which warehouses can be used for picking up goods, as well as the inventory status of goods in each warehouse, to ensure that the warehouse selected in the allocation plan has sufficient inventory to meet the needs of the dispatch order. The warehouse capacity limit defines the maximum amount of goods that each warehouse can handle per unit time, to avoid overloading the warehouse and ensure the feasibility of the allocation plan. The inter-warehouse distance provides distance information between warehouses, which can be input in the form of an inter-warehouse distance matrix to calculate transportation costs or optimize transportation routes, and supports distance calculations in optimization objectives, such as minimizing the total transportation distance. The commodity detail collection is used to clarify the types and quantities of goods that need to be picked up for each dispatch order, provide specific requirements for warehouse allocation, and ensure that the allocation plan can meet the requirements of the dispatch order.

[0056] In addition, it should be noted that the minimum total number of pick-up warehouses is used to minimize the number of warehouses involved in the allocation, which can reduce the use cost and management complexity of the warehouses. The shortest total distance of the pick-up warehouses is used to minimize the total transportation distance between warehouses, which can reduce transportation costs and improve transportation efficiency.

[0057] In a feasible implementation manner, the step of determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a plurality of vehicle dispatch orders includes: Step S30111: if the warehouse allocation request is to consider the warehouse capacity limit, then determine the allocation decision variables according to the available warehouse set and inventory details, warehouse capacity limit and commodity detail set; It is understandable that in order to ensure that the allocation decision variables can reflect the capacity constraints of the warehouse and avoid overload allocation, if the warehouse allocation request needs to consider the warehouse capacity limit, then the determination of the decision variables needs to be combined with the set of available warehouses, inventory details, warehouse capacity limit and the set of commodity details of the dispatch order. The decision variables will consider the capacity limit of each warehouse, limit the allocation amount of each warehouse, and ensure that the allocation plan is feasible within the capacity range and will not be overloaded.

[0058] Step S30112: if the warehouse allocation request is to consider the distance to the pickup warehouse, determine the allocation decision variables according to the set of available pickup warehouses and inventory details, the distance between warehouses and the set of commodity details; It is understandable that in order to ensure that the allocation decision variables can reflect the distance information between warehouses in order to optimize the transportation route, if the warehouse allocation request needs to consider the distance to the pickup warehouse, the determination of the decision variables needs to be combined with the set of available pickup warehouses, inventory details, distances between warehouses, and the set of commodity details of the dispatch order. The decision variables will take into account the distance between warehouses, provide support for subsequent optimization goals (such as minimizing the total transportation distance), and help reduce transportation costs.

[0059] Step S30113, if the warehouse allocation request takes into account the warehouse capacity limit and the distance to the pickup warehouse, the allocation decision variables are determined based on the set of available pickup warehouses and inventory details, the warehouse capacity limit, the distance between warehouses and the set of commodity details.

[0060] It is understandable that in order to ensure that the allocation decision variables can meet the requirements of capacity constraints and distance optimization at the same time, if the warehouse allocation request needs to consider both the warehouse capacity limit and the distance to the pickup warehouse, then the determination of the decision variables needs to comprehensively consider the set of available pickup warehouses, inventory details, warehouse capacity limit, distance between warehouses, and the set of commodity details of the dispatch order. The decision variables will consider both capacity and distance factors, comprehensively consider capacity and distance, and ensure that the allocation plan can optimize the transportation path while meeting the capacity constraints.

[0061] In this implementation, when considering the warehouse capacity limit, the decision variables will be combined with the capacity limit to ensure that the allocation plan will not be overloaded. When considering the distance to the pickup warehouse, the decision variables will be combined with the distance information to optimize the transportation path. When considering both capacity and distance, the decision variables will comprehensively consider both and balance management costs and transportation costs. Not only can the decision variables be determined quickly, but also flexible and reliable solutions can be provided in complex logistics scenarios, which can significantly improve the efficiency and rationality of warehouse allocation and reduce operating costs.

[0062] For example, Figure 2 As shown, Figure 2 A flow chart of the mixed integer programming model construction provided in the first embodiment of the warehouse allocation method of this application. Taking four warehouse allocation optimization situations as examples, specifically: 1. Input the allocation cycle as days, configure without considering warehouse capacity, and do not consider whether the pickup warehouse is closer.

[0063] S1: Obtain the basic data required by the model, including the set of dispatch orders within the allocation period, the quantity details of the goods in each dispatch order, the set of warehouses that can be picked up, and the inventory details of the goods in each warehouse; S2: Constructing a mixed integer programming model. Based on the configuration information input in step S2, the dispatch order information and inventory information in the basic data, a mixed integer programming model is established; the establishment of the model includes: 1. Parameter description: : SKU (Stock Keeping Unit, product) collection.

[0064] : A collection of warehouses where you can pick up goods.

[0065] : Departure order collection.

[0066] SKU In warehouse The total inventory in .

[0067] SKU In the departure list The number in .

[0068] M: represents a maximum value, an auxiliary constant used in modeling.

[0069] 2. Variable description: :warehouse Assign to dispatch order SKUs The number of .

[0070] :Departure Order Do you want to Pick up goods, .

[0071] 3. Model objectives: First goal: fewer pick-up warehouses:

[0072] 4. Constraints: The dispatch order requirement satisfies the constraints:

[0073] Base warehouse inventory matching constraints:

[0074] The shipment order will only have the quantity of the SKU if the goods are picked up from the warehouse:

[0075] 2. Enter the allocation cycle as days, configure the warehouse capacity, and do not consider the closer distance of the pickup warehouse.

[0076] S1: Obtain the basic data required by the model, including the set of dispatch orders within the allocation period, the quantity details of the goods in each dispatch order, the set of warehouses that can be picked up, the inventory details of the goods in each warehouse, and the production capacity limit of each warehouse (i.e. the maximum number of outbound items); S2: Construct a mixed integer programming model. According to the configuration information input in step S2, the dispatch order information and inventory information in the basic data, a mixed integer programming model is established; the model establishment process is as follows: 1. Parameter description: : SKU (Stock Keeping Unit, product) collection.

[0077] : A collection of warehouses where you can pick up goods.

[0078] : Departure order collection.

[0079] SKU In warehouse The total inventory in .

[0080] :warehouse production capacity ceiling.

[0081] SKU In the departure list The number in .

[0082] M: represents a maximum value, an auxiliary constant used in modeling.

[0083] 2. Variable description: :warehouse Assign to dispatch order SKUs The number of .

[0084] :Departure Order Do you want to Pick up goods, .

[0085] 3. Model objectives: First goal: fewer pick-up warehouses:

[0086] 4. Constraints: The dispatch order requirement satisfies the constraints:

[0087] Base warehouse inventory matching constraints:

[0088] If the warehouse capacity limit is considered, there is a warehouse capacity limit constraint:

[0089] The shipment order will only have the quantity of the SKU if the goods are picked up from the warehouse:

[0090] 3. Input the allocation cycle as days, configure without considering warehouse capacity, and consider the pickup warehouse to be closer.

[0091] S1: Obtain the basic data required by the model. Including the set of dispatch orders within the allocation period, the quantity details of the goods in each dispatch order, the set of warehouses that can be picked up, the inventory details of the goods in each warehouse, and the distance matrix between warehouses (that is, the distance information between all pickup warehouses, which needs to be obtained if the configuration described in S1 considers that the pickup warehouse is closer); S2: Constructing a mixed integer programming model. Based on the configuration information input in step S2, the dispatch order information and inventory information in the basic data, a mixed integer programming model is established; the establishment of the model includes: 1. Parameter description: : SKU (Stock Keeping Unit, product) collection.

[0092] : A collection of warehouses where you can pick up goods.

[0093] : Departure order collection.

[0094] SKU In warehouse The total inventory in .

[0095] :warehouse Wakura The distance between.

[0096] SKU In the departure list The number in .

[0097] M: represents a maximum value, an auxiliary constant used in modeling.

[0098] 2. Variable description: :warehouse Assign to dispatch order SKUs The number of .

[0099] :Departure Order Do you want to Pick up goods, .

[0100] :Departure Order Whether to use the same warehouse Wakura Pick up goods, .

[0101] :Departure Order The maximum transportation distance between the pick-up warehouses, .

[0102] 3. Model objectives: First goal: fewer pick-up warehouses:

[0103] Second goal: smaller distance between delivery warehouses:

[0104] 4. Constraints: The dispatch order requirement satisfies the constraints:

[0105] Base warehouse inventory matching constraints:

[0106] The shipment order will only have the quantity of the SKU if the goods are picked up from the warehouse:

[0107] Variable relationship constraints:

[0108]

[0109] 4. Enter the allocation cycle as days, configure the warehouse capacity, and consider the pickup warehouse to be closer.

[0110] S1: Obtain the basic data required by the model. Including the set of dispatch orders within the allocation period, the quantity details of the goods in each dispatch order, the set of warehouses that can be picked up, the inventory details of the goods in each warehouse, the production capacity limit of each warehouse (i.e. the maximum number of outbound items), and the distance matrix between warehouses (i.e. the distance information between all pickup warehouses); S2: Construct a mixed integer programming model. According to the configuration information input in step S2, the dispatch order information and inventory information in the basic data, a mixed integer programming model is established; the model establishment process is as follows: 1. Parameter description: : SKU (Stock Keeping Unit, product) collection.

[0111] : A collection of warehouses where you can pick up goods.

[0112] : Departure order collection.

[0113] SKU In warehouse The total inventory in .

[0114] :warehouse production capacity ceiling.

[0115] :warehouse Wakura The distance between.

[0116] SKU In the departure list The number in .

[0117] M: represents a maximum value, an auxiliary constant used in modeling.

[0118] 2. Variable description: :warehouse Assign to dispatch order SKUs The number of .

[0119] :Departure Order Do you want to Pick up goods, .

[0120] :Departure Order Whether to use the same warehouse Wakura Pick up goods, .

[0121] :Departure Order The maximum transportation distance between the pick-up warehouses, .

[0122] 3. Model objectives: First goal: fewer pick-up warehouses:

[0123] Second goal: smaller distance between delivery warehouses:

[0124] 4. Constraints: The dispatch order requirement satisfies the constraints:

[0125] Base warehouse inventory matching constraints:

[0126] Warehouse capacity upper limit constraints:

[0127] The shipment order will only have the quantity of the SKU if the goods are picked up from the warehouse:

[0128] Variable relationship constraints:

[0129]

[0130] In a feasible implementation manner, the step of obtaining the dispatch order warehouse allocation result according to the model allocation result includes: Step S3041, rounding the model allocation result to obtain a rounded model allocation result; It should be noted that the model allocation result is the original allocation result output by the model solver after solving the model, which may contain continuous variables. The rounding process can convert the continuous variable results into integers.

[0131] It is understandable that the model allocation results may contain solutions for continuous variables (for example, the number of goods extracted from a warehouse in a dispatch order may be a decimal), but in actual operations, the number of goods must be an integer. Therefore, it is necessary to round the model allocation results to convert the continuous variable results output by the model into integer results that are feasible in actual operations, to ensure that the allocation results meet actual needs and avoid inoperable decimal results.

[0132] Step S3042, based on the warehouse inventory corresponding to the dispatch order set, the allocation quantity of the rounded model allocation result is verified and corrected to obtain the dispatch order warehouse allocation result.

[0133] It should be noted that the warehouse inventory refers to the actual inventory quantity in each warehouse. Allocation quantity verification is used to verify whether the allocation result meets the warehouse inventory constraints, and to adjust the allocation result that exceeds the inventory by correction when the dispatch order does not meet the warehouse inventory constraints.

[0134] It is understandable that the allocation results after rounding need to be further verified to see if they are consistent with the actual inventory situation of the warehouse. If the allocation quantity of a warehouse exceeds its inventory, the allocation results need to be corrected to correct the unreasonable allocation that may be caused by rounding or model errors, to ensure that the allocation results are within the constraints of the warehouse inventory, to avoid the inability to execute the allocation plan due to insufficient inventory, and to ensure the feasibility of the allocation plan.

[0135] In this implementation, the model allocation results are first rounded to ensure that the allocated quantity is an integer and meets the actual operational requirements. The rounded results are then verified and corrected based on the warehouse inventory to ensure the feasibility of the allocation plan. This not only allows the model results to be quickly converted into actual plans, but also provides flexible and reliable solutions in complex logistics scenarios.

[0136] For example, Figure 3 As shown, Figure 3 The flowchart of the model solution and result conversion provided in the first embodiment of the warehouse allocation method of this application. Combining the above four warehouse allocation optimization situations, after the model is established, the model can be solved using the commercial solver CPLEX or Gurobi. After the model is solved, the variables obtained by the model solution are And variables The value is converted into specific delivery details and output to the delivery details table of the dispatch order. The specific process of result verification and conversion is as follows: 1. Initialize the warehouse available inventory. Record the current SKU In warehouse The remaining available inventory in ; 2. Round up the allocated quantity.

[0137] 1) Traversal The model results Round up. For rounding Assign to dispatch order SKUs The number of , update current inventory information ; 3. Check and correct the quantity allocated on the dispatch order. Products , check the allocation quantity of all warehouses and the corresponding SKU quantity of the dispatch order Whether it matches or not, the specific process is as follows: For each dispatch Products , perform the following steps: 1) If = , that is, the allocation quantity of all warehouses is equal to the SKU quantity corresponding to the dispatch order. The current dispatch order Products The verification passed.

[0138] 2) If < , that is, the allocation quantity of all warehouses is less than the SKU quantity corresponding to the dispatch order, and the quantity to be allocated of product i of the current dispatch order k is calculated ; Repeat the following steps N times to fill the allocated number of vacancies: Choose one of all warehouses with inventory balance greater than 0. Bins greater than 0 ,make ; Update current inventory information .

[0139] 3) If > , that is, the allocation quantity of all warehouses is greater than the SKU quantity corresponding to the dispatch order, and the quantity to be allocated of product i of the current dispatch order k is calculated ; Repeat the following steps N times to handle the allocated number of redundancies: All bins greater than 0 Sort by size in ascending order, select the first bin in the list ,make ; Update current inventory information .

[0140] 4. Output the delivery list of the dispatch order. , if greater than 0, it is a warehouse Assign to dispatch order SKUs The quantity is output to the departure details table.

[0141] This embodiment provides a warehouse allocation method, which first receives a warehouse allocation request as the starting point of the entire allocation process and triggers subsequent allocation operations; then, according to the warehouse allocation request, obtains all the dispatch orders that need to allocate warehouses to integrate the necessary data required for warehouse allocation; finally, using a mixed integer programming algorithm, the warehouse allocation problem of the dispatch order is modeled as an optimization problem, and warehouse allocation is performed to obtain the dispatch order warehouse allocation result, thereby achieving efficient and reasonable warehouse allocation. The dispatch order warehouse allocation based on the mixed integer programming algorithm is implemented, which solves the problem of low logistics efficiency of the existing warehouse allocation method and improves the logistics transportation efficiency.

[0142] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the warehouse allocation method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0143] This application also provides a warehouse distribution device, please refer to Figure 4 , the cargo compartment allocation device comprises: A request receiving module 10, for receiving a cargo warehouse allocation request; A dispatch order acquisition module 20 is used to acquire a dispatch order set to be allocated to a cargo warehouse according to the cargo warehouse allocation request, wherein the dispatch order set includes a plurality of dispatch orders; The cargo warehouse allocation module 30 is used to perform cargo warehouse allocation based on a mixed integer programming algorithm according to preset cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders, and obtain a dispatch order cargo warehouse allocation result.

[0144] Optionally, the cargo warehouse allocation module 30 is further used for: Generate an objective function and constraints based on the cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders; A model is constructed based on the objective function and constraint conditions to obtain a warehouse allocation model; Solving the warehouse allocation model by using a preset integer programming model solver to obtain a model allocation result; According to the allocation result of the model, the dispatch order warehouse allocation result is obtained.

[0145] Optionally, the cargo warehouse allocation module 30 is further used for: Determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders; Determining an optimization target according to the warehouse allocation request; Based on the allocation decision variables and the optimization goal, an objective function and constraints are generated.

[0146] Optionally, the warehouse configuration information includes one or more of a set of pick-up warehouses and inventory details, an upper limit on warehouse capacity and distances between warehouses; the dispatch order includes a set of commodity details; and the optimization goal includes one or more of a minimum total number of pick-up warehouses and the shortest total distances between pick-up warehouses.

[0147] Optionally, the cargo warehouse allocation module 30 is further used for: If the warehouse allocation request is to consider the warehouse capacity limit, then determine the allocation decision variables according to the set of available warehouses and inventory details, the warehouse capacity limit and the commodity details set; If the warehouse allocation request is to consider the distance to the pickup warehouse, then determine the allocation decision variables according to the set of available pickup warehouses and inventory details, the distance between warehouses and the set of commodity details; If the warehouse allocation request takes into account the warehouse capacity limit and the distance to the pickup warehouse, the allocation decision variables are determined based on the set of available pickup warehouses and inventory details, the warehouse capacity limit, the distance between warehouses and the set of commodity details.

[0148] Optionally, the cargo warehouse allocation module 30 is further used for: Rounding the model allocation result to obtain a rounded model allocation result; According to the warehouse inventory corresponding to the dispatch order set, the allocation quantity of the rounded model allocation result is verified and corrected to obtain the dispatch order warehouse allocation result.

[0149] The cargo warehouse allocation device provided by the present application adopts the cargo warehouse allocation method in the above embodiment, which can solve the technical problem of low logistics efficiency of the existing cargo warehouse allocation method. Compared with the prior art, the beneficial effects of the cargo warehouse allocation device provided by the present application are the same as the beneficial effects of the cargo warehouse allocation method provided by the above embodiment, and the other technical features in the cargo warehouse allocation device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0150] The present application provides a cargo warehouse allocation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable 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 cargo warehouse allocation method in the first embodiment described above.

[0151] Reference below Figure 5 , which shows a schematic diagram of the structure of a warehouse allocation device suitable for implementing the embodiment of the present application. The warehouse allocation 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 cargo storage allocation 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.

[0152] like Figure 5As shown, the warehouse distribution device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory 1002 or the program loaded from the storage device 1003 to the random access memory 1004. In the random access memory 1004, various programs and data required for the operation of the warehouse distribution device are also stored. The processing device 1001, the read-only memory 1002 and the random access memory 1004 are connected to each other through a bus 1005. The input / output interface 1006 is also connected to the bus. Generally, the following systems can be connected to the input / output interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, 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 warehouse allocation device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a warehouse allocation 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 have alternatively.

[0153] 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 read-only memory 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.

[0154] The cargo warehouse allocation device provided by the present application adopts the cargo warehouse allocation method in the above embodiment, which can solve the technical problem of low logistics efficiency of the existing cargo warehouse allocation method. Compared with the prior art, the beneficial effects of the cargo warehouse allocation device provided by the present application are the same as the beneficial effects of the cargo warehouse allocation method provided by the above embodiment, and the other technical features in the cargo warehouse allocation device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0155] 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.

[0156] 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.

[0157] 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 warehouse allocation method in the above-mentioned embodiment.

[0158] 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 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 that can be used by or in combination with an instruction execution 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.

[0159] The computer-readable storage medium may be included in the cargo warehouse allocation device; or may exist independently without being assembled into the cargo warehouse allocation device.

[0160] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the warehouse allocation device, the warehouse allocation device enables the following: to receive a warehouse allocation request; based on the warehouse allocation request, obtain a set of dispatch orders to be allocated to the warehouse, wherein the set of dispatch orders includes several dispatch orders; based on a mixed integer programming algorithm, perform warehouse allocation according to preset warehouse configuration information, the warehouse allocation request and several dispatch orders, and obtain a dispatch order warehouse allocation result.

[0161] 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).

[0162] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a 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 box can also occur in a different order from the order marked in the accompanying drawings. For example, two 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 box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart 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.

[0163] The modules involved in the embodiments of the present application may be implemented by software or hardware, wherein the name of the module does not limit the unit itself in some cases.

[0164] 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 warehouse allocation method, and can solve the technical problem of low logistics efficiency of the existing warehouse allocation method. 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 warehouse allocation method provided by the above-mentioned embodiment, and will not be repeated here.

[0165] The present application also provides a computer program product, comprising a computer program, which implements the steps of the above-mentioned warehouse allocation method when executed by a processor.

[0166] The computer program product provided by this application can solve the technical problem of low logistics efficiency of the existing warehouse allocation method. 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 warehouse allocation method provided by the above embodiment, which will not be repeated here.

[0167] 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 warehouse allocation method, characterized in that: The method comprises: Receive warehouse allocation requests; According to the cargo warehouse allocation request, a set of dispatch orders to be allocated to the cargo warehouse is obtained, wherein the set of dispatch orders includes a plurality of dispatch orders; Based on a mixed integer programming algorithm, warehouse allocation is performed according to preset warehouse configuration information, the warehouse allocation request and a number of dispatch orders to obtain a dispatch order warehouse allocation result.

2. The method according to claim 1, characterized in that: The step of performing warehouse allocation based on the mixed integer programming algorithm according to the preset warehouse configuration information, the warehouse allocation request and a number of dispatch orders to obtain the dispatch order warehouse allocation result includes: Generate an objective function and constraints based on the cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders; A model is constructed based on the objective function and constraint conditions to obtain a warehouse allocation model; Solving the warehouse allocation model by using a preset integer programming model solver to obtain a model allocation result; According to the allocation result of the model, the dispatch order warehouse allocation result is obtained.

3. The method according to claim 2, characterized in that: The step of generating the objective function and constraint conditions according to the cargo warehouse configuration information, the cargo warehouse allocation request and the plurality of vehicle dispatch orders comprises: Determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders; Determining an optimization target according to the warehouse allocation request; Based on the allocation decision variables and the optimization goal, an objective function and constraints are generated.

4. The method according to claim 3, characterized in that: The warehouse configuration information includes one or more of a set of pickup warehouses and inventory details, an upper limit on warehouse capacity, and distances between warehouses; the dispatch order includes a set of commodity details; and the optimization goal includes one or more of a minimum total number of pickup warehouses and the shortest total distances between pickup warehouses.

5. The method according to claim 4, characterized in that: The step of determining allocation decision variables according to the cargo warehouse configuration information, the cargo warehouse allocation request and a plurality of vehicle dispatch orders comprises: If the warehouse allocation request is to consider the warehouse capacity limit, then determine the allocation decision variables according to the set of available warehouses and inventory details, the warehouse capacity limit and the commodity details set; If the warehouse allocation request is to consider the distance to the pickup warehouse, then determine the allocation decision variables according to the set of available pickup warehouses and inventory details, the distance between warehouses and the set of commodity details; If the warehouse allocation request takes into account the warehouse capacity limit and the distance to the pickup warehouse, the allocation decision variables are determined based on the set of available pickup warehouses and inventory details, the warehouse capacity limit, the distance between warehouses and the set of commodity details.

6. The method according to claim 2, characterized in that: The step of obtaining the dispatch order warehouse allocation result according to the model allocation result comprises: Rounding the model allocation result to obtain a rounded model allocation result; According to the warehouse inventory corresponding to the dispatch order set, the allocation quantity of the rounded model allocation result is verified and corrected to obtain the dispatch order warehouse allocation result.

7. A cargo storage distribution device, characterized in that: The device comprises: A request receiving module, used for receiving a warehouse allocation request; A dispatch order acquisition module, used to acquire a dispatch order set to be allocated to the cargo warehouse according to the cargo warehouse allocation request, wherein the dispatch order set includes a plurality of dispatch orders; The cargo warehouse allocation module is used to perform cargo warehouse allocation based on a mixed integer programming algorithm according to preset cargo warehouse configuration information, the cargo warehouse allocation request and a number of dispatch orders, and obtain a dispatch order cargo warehouse allocation result.

8. A warehouse distribution 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 cargo warehouse allocation method according to any one of claims 1 to 6.

9. 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 warehouse allocation method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the warehouse allocation method according to any one of claims 1 to 6 are implemented.

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