Logistics warehouse management method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a logistics warehouse management method and device, electronic equipment and a storage medium, and relates to the technical field of logistics management, and the method comprises the steps: obtaining the warehouse information of a logistics warehouse at the current moment; obtaining a linear programming model for the logistics warehouse and a constraint condition for the linear programming model, and processing the warehouse information according to the linear programming model and the constraint condition to obtain a warehouse management strategy for the logistics warehouse; and according to the warehouse management strategy, adjusting the warehouse layout and the warehouse-out operation process of the logistics warehouse, thereby optimizing the storage scheme of the warehouse by introducing a linear programming method, so as to improve the storage space utilization rate of the warehouse, reduce the goods taking time and cost, realize the automation and intelligence of the warehouse, and reduce human intervention and errors.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management, and in particular to a logistics warehouse management method, a logistics warehouse management device, an electronic device and a computer-readable storage medium. Background Art

[0002] With the rapid development of e-commerce and logistics industries, warehouse management has become increasingly important in the supply chain. In the process of warehouse management, people often rely on past experience and simple management rules, which makes it difficult to cope with complex and changing inventory needs, resulting in low storage space utilization, poor operating efficiency, and cargo accumulation. Summary of the invention

[0003] The embodiments of the present invention provide a logistics warehouse management method, device, electronic device and computer-readable storage medium to solve or partially solve the problems of low storage space utilization, poor operating efficiency and easy accumulation of goods in the warehouse.

[0004] The embodiment of the present invention discloses a logistics warehouse management method, including:

[0005] Get the current warehouse information of the logistics warehouse;

[0006] Obtaining a linear programming model for the logistics warehouse and constraints for the linear programming model, processing the warehouse information according to the linear programming model and the constraints, and obtaining a warehouse management strategy for the logistics warehouse;

[0007] The warehouse layout and outbound operation process of the logistics warehouse are adjusted according to the warehouse management strategy.

[0008] In some feasible implementations, the constraint conditions at least include storage constraint conditions, cargo constraint conditions, and first-in-first-out constraint conditions. The storage constraint conditions indicate that one cargo is stored in the same storage location in the logistics warehouse. The cargo constraint conditions indicate that each cargo is stored in only one location. The first-in-first-out constraint conditions indicate that the cargo first stored in the logistics warehouse is taken out first. The warehouse information is processed according to the linear programming model and the constraint conditions to obtain a warehouse management strategy for the logistics warehouse, including:

[0009] The warehouse information is processed according to the linear programming model, the storage constraint condition, the cargo constraint condition and the first-in-first-out constraint condition to obtain a warehouse management strategy for the logistics warehouse.

[0010] In some feasible implementations, the warehouse information includes at least cargo information, location information, and cost information, and the processing of the warehouse information according to the linear programming model, the storage constraint, the cargo constraint, and the first-in-first-out constraint to obtain a warehouse management strategy for the logistics warehouse includes:

[0011] The cargo information, the location information and the cost information are input into the linear programming model for solving, and are constrained according to the storage constraints, the cargo constraints and the first-in-first-out constraints, and a warehouse management strategy for the logistics warehouse is output.

[0012] In some feasible implementations, the cargo information includes at least one of cargo batch, cargo entry time, cargo volume, cargo weight, cargo name and cargo number; the location information includes at least one of the orientation, size and distance from the entrance and exit corresponding to each storage location in the logistics warehouse; the cost information includes at least one of the storage cost, pickup cost and management cost of the goods.

[0013] In some feasible implementations, obtaining a linear programming model for the logistics warehouse includes:

[0014] Obtaining a decision variable, wherein the decision variable represents a storage state of the cargo at a target location;

[0015] An objective function for the decision variables is constructed, and the objective function is used as a linear programming model for the logistics warehouse. The objective function is used to characterize the total operating cost of the logistics warehouse.

[0016] In some feasible implementations, the objective function is:

[0017] min(Z)=sum(i)*sum(j)*(C(ij)*cdotG(ij))+sum(i)*sum(j)*(D(ij)*cdotW(ij));

[0018] Wherein, C(ij) is the unit storage cost of goods i stored at location j;

[0019] D(ij) is the unit cost of taking out the item i from the location j;

[0020] W(ij) is the state variable when the item i is taken out from the position j;

[0021] The sum(i)*sum(j)*(C(ij)*cdotG(ij)) is the total storage cost corresponding to the goods stored at each location;

[0022] The sum(i)*sum(j)*(D(ij)*cdotW(ij)) is the total cost of taking each item out from the storage location;

[0023] The min(Z) is the total operating cost.

[0024] In some feasible implementations, the warehouse management strategy includes at least the storage location and pickup order corresponding to each of the goods, and adjusting the warehouse layout and outbound operation process of the logistics warehouse according to the warehouse management strategy includes:

[0025] The storage position of the goods in the logistics warehouse is adjusted according to the storage position, and the goods are picked up according to the picking order, where the picking order represents that the goods that enter the logistics warehouse first are taken out first.

[0026] Some possible implementations also include:

[0027] Obtain the first warehouse storage cost and the first surplus stock of the logistics warehouse corresponding to the current moment and the second warehouse storage cost and the second surplus stock of the logistics warehouse corresponding to the target moment;

[0028] If the second surplus stock is greater than or equal to the first surplus stock, and / or the second warehouse storage cost is greater than the first warehouse storage cost, then obtaining parameter adjustment information for the linear programming model, and adjusting the target parameters in the linear programming model according to the parameter adjustment information to obtain a new linear programming model;

[0029] The target time is the time point when the warehouse management strategy is executed for a preset time, and the parameter adjustment information is the information for adjusting the parameters related to the cost information in the linear programming model.

[0030] The embodiment of the present invention further discloses a management device for a logistics warehouse, comprising:

[0031] Data acquisition module, used to obtain the warehouse information of the logistics warehouse at the current moment;

[0032] A model determination module, used to obtain a linear programming model for the logistics warehouse and constraints for the linear programming model, process the warehouse information according to the linear programming model and the constraints, and obtain a warehouse management strategy for the logistics warehouse;

[0033] The adjustment module is used to adjust the warehouse layout and outbound operation process of the logistics warehouse according to the warehouse management strategy.

[0034] In some feasible implementations, the constraint conditions at least include storage constraint conditions, cargo constraint conditions, and first-in-first-out constraint conditions. The storage constraint conditions represent that one cargo is stored in the same storage location in the logistics warehouse. The cargo constraint conditions represent that each cargo is stored in only one location. The first-in-first-out constraint conditions represent that the cargo first stored in the logistics warehouse is taken out first. The model determination module is specifically used for:

[0035] The warehouse information is processed according to the linear programming model, the storage constraint condition, the cargo constraint condition and the first-in-first-out constraint condition to obtain a warehouse management strategy for the logistics warehouse.

[0036] In some feasible implementations, the warehouse information includes at least cargo information, location information, and cost information, and the model determination module is specifically used to:

[0037] The cargo information, the location information and the cost information are input into the linear programming model for solving, and are constrained according to the storage constraints, the cargo constraints and the first-in-first-out constraints, and a warehouse management strategy for the logistics warehouse is output.

[0038] In some feasible implementations, the cargo information includes at least one of cargo batch, cargo entry time, cargo volume, cargo weight, cargo name and cargo number; the location information includes at least one of the orientation, size and distance from the entrance and exit corresponding to each storage location in the logistics warehouse; the cost information includes at least one of the storage cost, pickup cost and management cost of the goods.

[0039] In some feasible implementations, the model determination module is specifically used to:

[0040] Obtaining a decision variable, wherein the decision variable represents a storage state of the cargo at a target location;

[0041] An objective function for the decision variables is constructed, and the objective function is used as a linear programming model for the logistics warehouse. The objective function is used to characterize the total operating cost of the logistics warehouse.

[0042] In some feasible implementations, the objective function is:

[0043] min(Z)=sum(i)*sum(j)*(C(ij)*cdotG(ij))+sum(i)*sum(j)*(D(ij)*cdotW(ij));

[0044] Wherein, C(ij) is the unit storage cost of goods i stored at location j;

[0045] D(ij) is the unit cost of taking out the item i from the location j;

[0046] W(ij) is the state variable when the item i is taken out from the position j;

[0047] The sum(i)*sum(j)*(C(ij)*cdotG(ij)) is the total storage cost corresponding to the goods stored at each location;

[0048] The sum(i)*sum(j)*(D(ij)*cdotW(ij)) is the total cost of taking each item out from the storage location;

[0049] The min(Z) is the total operating cost.

[0050] In some feasible implementations, the warehouse management strategy includes at least the storage location and pickup order corresponding to each cargo, and the adjustment module is specifically used to:

[0051] The storage position of the goods in the logistics warehouse is adjusted according to the storage position, and the goods are picked up according to the picking order, where the picking order represents that the goods that enter the logistics warehouse first are taken out first.

[0052] Some possible implementations also include:

[0053] An information acquisition module, used to acquire the first warehouse storage cost and the first surplus stock of the logistics warehouse corresponding to the current moment and the second warehouse storage cost and the second surplus stock of the logistics warehouse corresponding to the target moment;

[0054] A model adjustment module, configured to obtain parameter adjustment information for the linear programming model if the second surplus stock is greater than or equal to the first surplus stock, and / or the second warehouse storage cost is greater than the first warehouse storage cost, and adjust the target parameters in the linear programming model according to the parameter adjustment information to obtain a new linear programming model;

[0055] The target time is the time point when the warehouse management strategy is executed for a preset time, and the parameter adjustment information is the information for adjusting the parameters related to the cost information in the linear programming model.

[0056] The embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0057] The memory is used to store computer programs;

[0058] The processor is used to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0059] The embodiment of the present invention further discloses a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, enables the processors to execute the method described in the embodiment of the present invention.

[0060] The embodiments of the present invention include the following advantages:

[0061] In an embodiment of the present invention, in the process of managing a logistics warehouse, for the goods currently stored in the logistics warehouse, the warehouse information of the logistics warehouse at the current moment can be obtained, and then a linear programming model for the logistics warehouse and constraints for the linear programming model are obtained, and the warehouse information is processed according to the linear programming model and the constraints to obtain a warehouse management strategy for the logistics warehouse, and then the warehouse layout and outbound operation process of the logistics warehouse are adjusted according to the warehouse management strategy, so as to optimize the storage plan of the warehouse by introducing a linear programming method, so as to improve the utilization rate of the warehouse storage space and reduce the accumulation of goods. At the same time, adjusting the outbound operation process can improve the efficiency of goods in and out of the warehouse, reduce the time and cost of picking up goods, and realize warehouse automation and intelligence, and reduce human intervention and errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a flow chart of the steps of a logistics warehouse management method provided in an embodiment of the present invention;

[0063] Figure 2 is a schematic diagram of the management process of a logistics warehouse provided in an embodiment of the present invention;

[0064] Figure 3 is a structural block diagram of a logistics warehouse management device provided in an embodiment of the present invention;

[0065] Figure 4 It is a block diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] With the rapid development of e-commerce and logistics industries, warehouse management has become increasingly important in the supply chain. Traditional warehouse management methods rely on experience and simple rules, which are difficult to cope with complex and changing inventory needs, resulting in low storage space utilization, poor operating efficiency, and cargo accumulation.

[0068] For example, the rise of e-commerce has brought about a surge in order volume and a diversification of order types, which has put higher demands on warehouse management. Traditional warehouse management often adopts a static storage strategy and cannot flexibly adjust the inventory layout according to real-time data and market changes, resulting in a waste of storage space. For example, some hot-selling products may extend the picking time due to poor storage locations, while unpopular products may occupy valuable storage space. In addition, the rapid development of the logistics industry also requires warehouse management to be more efficient and precise. Traditional warehouse operations often rely on manual labor, which is not only inefficient but also prone to errors. During peak periods, warehouses may be short of staff, resulting in the speed of cargo processing failing to keep up with the speed of order growth, which in turn affects the efficiency of the entire supply chain. In addition, manual operations also make it difficult to achieve precise control of inventory, and inaccurate inventory data may occur, leading to problems such as excess or shortage of inventory.

[0069] In this regard, in the present invention, in the process of managing the logistics warehouse, for the goods stored in the logistics warehouse at the current moment, the warehouse information of the logistics warehouse at the current moment can be obtained, and then a linear programming model for the logistics warehouse and constraints for the linear programming model are obtained, and the warehouse information is processed according to the linear programming model and the constraints to obtain a warehouse management strategy for the logistics warehouse, and then the warehouse layout and outbound operation process of the logistics warehouse are adjusted according to the warehouse management strategy, so as to optimize the storage plan of the warehouse by introducing the linear programming method, so as to improve the utilization rate of the warehouse storage space and reduce the accumulation of goods. At the same time, adjusting the outbound operation process can improve the efficiency of goods in and out of the warehouse, reduce the time and cost of picking up goods, and realize warehouse automation and intelligence, and reduce human intervention and errors.

[0070] Reference Figure 1 , shows a flow chart of the steps of a logistics warehouse management method provided in an embodiment of the present invention, which may specifically include the following steps:

[0071] Step 101, obtaining the current warehouse information of the logistics warehouse;

[0072] In the process of intelligent management of logistics warehouses, data related to goods can be collected so as to perform automated and intelligent management of goods in the logistics warehouse based on the collected data.

[0073] Optionally, the logistics warehouse related data can be collected in the following ways:

[0074] 1. Barcode and RFID (Radio Frequency Identification) technology can quickly and accurately identify and track goods by attaching barcodes or RFID tags to each item or package. Barcode scanning and RFID reading equipment can automatically collect information about goods entering and leaving the warehouse, and realize real-time positioning and status monitoring of goods.

[0075] 2. Sensor technology: Deploying temperature, humidity, light, vibration and other sensors in the warehouse can monitor the storage environment of goods in real time and ensure that the goods are stored in suitable conditions. The data collected by these sensors can help prevent damage and quality degradation of goods.

[0076] 3. Automated equipment: Automated warehouses, conveyor lines, sorting robots and other equipment can automatically record the movement trajectory and operation history of goods, and provide accurate data on goods location and operation time.

[0077] 4. Warehouse Management System (WMS): WMS is the core system for warehouse data collection. It can integrate various data collection devices, update inventory data in real time, and provide functions such as inventory query, order processing, and report generation. WMS can also be integrated with other enterprise resource planning (ERP) systems to achieve data sharing and circulation.

[0078] It should be noted that the collected data needs to be processed through data analysis tools to extract valuable information, such as inventory turnover rate, cargo retention time, operational efficiency and other indicators. These analysis results can help warehouse managers optimize inventory structure, improve operational efficiency and reduce costs. In addition, in the process of collecting and processing cargo data, it is necessary to ensure the security and privacy of the data to prevent data leakage and abuse. This includes using encryption technology to protect data transmission, establishing strict data access permission control, and complying with relevant data protection regulations.

[0079] In the embodiment of the present invention, the warehouse information corresponding to the current moment of the logistics warehouse can be collected, and the warehouse information can be cleaned and preprocessed to ensure the accuracy and integrity of the data. Optionally, the determination of the warehouse storage strategy is not a fixed strategy, but a result that can be dynamically determined for different goods, different storage requirements and different storage costs of the logistics warehouse at different times, so that by dynamically adjusting the warehouse management strategy, the storage plan of the warehouse can be optimized by introducing a linear programming method.

[0080] Optionally, for warehouse information cleaning, duplicate entries in the database can be checked and deleted to avoid repeated calculations and analysis errors, and obviously erroneous data such as negative inventory and temperature readings outside a reasonable range can be identified and corrected or deleted. For missing data, filling (such as using the mean, median or mode) or deleting related records can be selected according to actual conditions, and data formats such as date format, unit, coding, etc. can be unified to ensure data consistency and comparability. For warehouse information preprocessing, data can be converted into a form more suitable for analysis, such as converting categorical variables into numerical variables, or discretizing continuous variables, normalizing numerical data to make them fall into the same numerical range to facilitate subsequent statistical analysis and machine learning model training, selecting the most valuable features for the analysis target from a large number of data features, removing redundant and irrelevant features to improve analysis efficiency and accuracy, and for high-dimensional data, methods such as principal component analysis can be used for dimensionality reduction to reduce the complexity of the data while retaining the main information. In addition, after completing the cleaning and preprocessing of the data, you can also perform logical checks to ensure that the data is logically reasonable, such as the inventory quantity cannot exceed the warehouse capacity, the goods outbound time cannot be earlier than the goods inbound time, etc., and perform consistency checks to ensure the accuracy of data updates and synchronization by checking the consistency of data between different systems or different time points.

[0081] Step 102, obtaining a linear programming model for the logistics warehouse and constraints for the linear programming model, processing the warehouse information according to the linear programming model and the constraints, and obtaining a warehouse management strategy for the logistics warehouse;

[0082] After collecting the warehouse information currently corresponding to the logistics warehouse, we can further obtain the linear programming model for the logistics warehouse and the constraints of the linear programming model, and then process the warehouse information according to the linear programming model and the constraints to obtain the warehouse management strategy corresponding to the current moment of the logistics warehouse, so as to manage the logistics warehouse based on the warehouse management strategy. By introducing the linear programming method, the storage plan of the warehouse is optimized to improve the utilization rate of the warehouse storage space and reduce the accumulation of goods.

[0083] In some feasible implementations, the decision variables may be obtained first, which represent the storage status of the goods at the target location, and then the objective function for the decision variables may be constructed, and the objective function may be used as a linear programming model for the logistics warehouse, and the objective function may be used to represent the total operating cost of the logistics warehouse. The objective function may be:

[0084] min(Z) = sum(i)*sum(j)*(C(ij)*cdotG(ij)) + sum(i)*sum(j)*(D(ij)*cdotW(ij));

[0085] Wherein, C(ij) is the unit storage cost of storing cargo i at location j; D(ij) is the unit picking cost of picking up cargo i from location j; W(ij) is the state variable when cargo i is picked up from location j; sum(i)*sum(j)*(C(ij)*cdotG(ij)) is the total storage cost corresponding to the cargoes stored at each location; sum(i)*sum(j)*(D(ij)*cdotW(ij)) is the total picking cost corresponding to each cargo being picked up from the location where it is stored; min(Z) is the total operation cost. In addition, the decision variable can be G(ij), representing the storage state of cargo i at location j. If cargo i is at location j, then G(ij) = 1; if cargo i is not at location j, then G(ij) = 0. Thus, by constructing a linear programming model, the storage plan of the warehouse can be optimized, improving the utilization rate of the warehouse storage space to reduce cargo accumulation.

[0086] After determining the linear programming model, the constraint conditions for the linear programming model can also be determined, and the solution process can be constrained through the constraint conditions to improve the accuracy of model prediction. Among them, the constraint conditions at least include storage constraint conditions, cargo constraint conditions, and first-in-first-out constraint conditions. The storage constraint conditions represent that only one cargo is stored at the same storage location in the logistics warehouse. The cargo constraint conditions represent that each cargo is stored at only one location. The first-in-first-out constraint conditions represent that the cargoes stored in the logistics warehouse earlier are picked up first.

[0087] In some examples, the storage constraint can be used to represent that only one cargo is stored at the same storage location in the logistics warehouse, that is, [sum(i)×G(ij) = 1 ∀j]; the cargo constraint is used to represent that each cargo is stored at only one location, that is, [sum(j)×G(ij) = 1 ∀i]; the first-in-first-out constraint can be that the cargoes stored in the logistics warehouse earlier are picked up first. Assuming t(i) is the storage time of cargo i and t(j) is the storage time of cargo j, if t(i) < t(j), then [W(ij) if t(i) < t(j)] needs to be satisfied. Thus, by setting the constraint conditions, the prediction process of the linear programming model is constrained to improve the accuracy of model prediction.

[0088] After obtaining the linear programming model and various constraints, the warehouse information can be processed according to the linear programming model, storage constraints, cargo constraints and first-in-first-out constraints to obtain a warehouse management strategy for the logistics warehouse. By introducing the linear programming method, the storage plan of the warehouse is optimized so that the logistics warehouse can be effectively managed based on the optimized warehouse management strategy.

[0089] In a specific implementation, the warehouse information may at least include cargo information, location information, and cost information. The cargo information, location information, and cost information may then be input into a linear programming model for solution, and constrained according to storage constraints, cargo constraints, and first-in-first-out constraints, to output a warehouse management strategy for a logistics warehouse. Among them, cargo information includes at least one of cargo batch, cargo entry time, cargo volume, cargo weight, cargo name, and cargo number; location information includes at least one of the corresponding orientation, size, and distance from the entrance and exit of each storage location in the logistics warehouse; cost information includes at least one of the storage cost, pickup cost, and management cost of the cargo.

[0090] It should be noted that cargo batch refers to the cargo produced in the same batch, which usually has the same production date, production location and production conditions, which helps to track the origin and quality of the cargo; cargo entry time refers to the specific time when the cargo enters the warehouse, which is crucial for inventory management strategies such as first-in-first-out or last-in-first-out; cargo volume refers to the three-dimensional size of the cargo, usually in cubic meters (m 3 ) is used to calculate storage space requirements and optimize warehouse layout; Cargo weight: the mass of the cargo, usually in kilograms (kg), which affects the handling and transportation costs of the cargo; Cargo name: the specific name or description of the cargo, used to identify and classify the cargo; Cargo number: a unique cargo identification code, usually a barcode or RFID tag, used to quickly retrieve and track the cargo; Location: the specific location of the storage location in the warehouse, such as the row, column, and layer of the shelf, which helps to determine the storage location of the cargo; Size: the size of the storage location, including length, width, and height, which is used to match the volume of the cargo to ensure that the cargo can be properly stored; Distance from the entrance and exit: the distance between the storage location and the warehouse entrance and exit affects the efficiency of cargo entry and exit and the handling cost; Storage cost: the cost incurred by storing the cargo in the warehouse, including rent, energy consumption, insurance, etc.; Pickup cost: the cost incurred by taking the cargo out of the warehouse, including labor, equipment use, time, etc.; Management cost: the cost incurred in the warehouse management process, including employee wages, system maintenance, administrative expenses, etc., which the present invention does not limit.

[0091] In one example, based on the above linear programming model and constraints, the cargo information, location information, and cost information can be input into the linear programming model for linear programming solution to determine the warehouse management strategy corresponding to the minimum value of the objective function. For example, for a logistics warehouse, there are 5 cargoes and 5 storage locations, and the relevant data is as follows:

[0092] Cargo information:

[0093] Cargo 1: Volume = 2m 3 , weight = 10kg, storage time = 1 day ago

[0094] Cargo 2: Volume = 3m 3 , weight = 15kg, storage time = 2 days ago

[0095] Cargo 3: Volume = 1m 3 , weight = 5kg, storage time = 3 days ago

[0096] Cargo 4: Volume = 4m 3 , weight = 20kg, storage time = 4 days ago

[0097] Cargo 5: Volume = 2m 3 , weight = 10kg, storage time = 5 days ago

[0098] Location Information:

[0099] Position 1: Volume capacity = 3m 3 , distance from entrance and exit = 10m

[0100] Position 2: Volume capacity = 4m 3 , distance from entrance and exit = 15m

[0101] Position 3: Volume capacity = 2m 3 , distance from entrance and exit = 5m

[0102] Position 4: Volume capacity = 5m 3 , distance from entrance and exit = 20m

[0103] Position 5: Volume capacity = 3m 3 , distance from entrance and exit = 10m

[0104] Cost Information:

[0105] Storage cost (C(ij)): Assume that the unit storage cost of each location is 1 yuan / m 3 / sky

[0106] Pickup cost (D(ij)): Assume that the unit pickup cost of each location is 0.1 yuan / m / kg

[0107] Then input the above information into the linear programming model for solution, and the corresponding warehouse management strategy can be obtained as follows:

[0108] G(1,3)=1 (goods 1 is stored at location 3)

[0109] G(2,1)=1 (goods 2 is stored at location 1)

[0110] G(3,5)=1 (goods 3 is stored at location 5)

[0111] G(4,2)=1 (goods 4 is stored at location 2)

[0112] G(5,4) = 1 (goods 5 is stored at location 4)

[0113] The total operating cost Z corresponding to the warehouse management strategy can be:

[0114] Storage cost = (21+31+11+41+2*1)*1 = 12 yuan

[0115] Pick-up cost = (1050.1+15100.1+5100.1+20150.1+10200.1) = 82.5 yuan

[0116] Total operating cost Z = 12 + 82.5 = 94.5 yuan.

[0117] Through the above process, the warehouse management strategy of the logistics warehouse is calculated by introducing the linear programming method, so as to optimize the storage plan of the warehouse through the warehouse management strategy, so as to improve the utilization rate of the warehouse storage space and reduce the accumulation of goods. In addition, the linear programming solution algorithm can include the simplex method and the interior point method, etc., which are not limited by the present invention.

[0118] Step 103: adjusting the warehouse layout and outbound operation process of the logistics warehouse according to the warehouse management strategy.

[0119] After determining the warehouse management strategy for the logistics warehouse at the current moment through the above process, the warehouse layout and outbound operation process of the logistics warehouse can be adjusted according to the warehouse management strategy, so as to optimize the storage plan of the warehouse by introducing linear programming methods, so as to improve the utilization rate of warehouse storage space and reduce cargo accumulation. At the same time, adjusting the outbound operation process can improve the efficiency of cargo in and out of the warehouse, reduce the time and cost of picking up goods, and realize warehouse automation and intelligence, reducing human intervention and errors.

[0120] In some feasible implementations, the warehouse management strategy at least includes the storage location and the order of picking up corresponding to each cargo. The storage location of the cargo in the logistics warehouse can be adjusted according to the storage location, and the cargo can be picked up in the order of picking up. The order of picking up represents that the cargo that enters the logistics warehouse first is taken out first. Therefore, by introducing the linear programming method, the storage plan of the warehouse can be optimized on the premise of satisfying the first-in-first-out principle, the utilization rate of the warehouse storage space can be improved, and the accumulation of cargo can be reduced; the efficiency of cargo entering and leaving the warehouse can be improved, and the time and cost of picking up cargo can be reduced; the cargo can be stored and retrieved in the order of first-in-first-out, and the quality and effectiveness of the cargo can be guaranteed; the automation and intelligence of the warehouse can be realized, and human intervention and errors can be reduced.

[0121] In one example, suppose there are four goods and four storage locations in a logistics warehouse, and the relevant data is as follows:

[0122] Cargo information:

[0123] Goods A: warehouse entry time = 1 day ago; Goods B: warehouse entry time = 2 days ago

[0124] Goods C: warehouse entry time = 3 days ago; Goods D: warehouse entry time = 4 days ago

[0125] Location Information:

[0126] Position 1: Distance to entrance and exit = 10m; Position 2: Distance to entrance and exit = 15m

[0127] Position 3: Distance to entrance and exit = 5m; Position 4: Distance to entrance and exit = 20m

[0128] Initial storage state:

[0129] Goods A: Location 1; Goods B: Location 2

[0130] Cargo C: Location 3; Cargo D: Location 4

[0131] The above is the current storage situation of the goods in the logistics warehouse. After the corresponding warehouse management strategy is calculated through the linear programming model, the storage location can be adjusted. According to the time of goods entering the warehouse, the goods that are expected to enter the warehouse first are stored in a location closer to the entrance and exit for quick pickup. Specifically, the adjusted storage location is as follows:

[0132] Goods D (earliest entry): Position 1

[0133] Cargo C: Location 2

[0134] Cargo B: Location 3

[0135] Goods A (latest entry): Location 4

[0136] Correspondingly, according to the adjusted storage location, the order of picking up goods should be consistent with the order of goods entering the warehouse, that is, first in, first out. Specifically, the order of picking up goods is as follows:

[0137] Cargo D (position 1); Cargo C (position 2); Cargo B (position 3); Cargo A (position 4).

[0138] The specific process of adjusting the storage location of goods can be:

[0139] Move item D from position 4 to position 1.

[0140] Move item C from position 3 to position 2.

[0141] Move item B from location 2 to location 3.

[0142] Move item A from position 1 to position 4.

[0143] When goods need to be picked up, first take out goods D from position 1, then take out goods C from position 2, then take out goods B from position 3, and finally take out goods A from position 4. By introducing the linear programming method, the storage plan of the warehouse can be optimized under the premise of satisfying the first-in-first-out principle, the utilization rate of warehouse storage space can be improved, and the accumulation of goods can be reduced; the efficiency of goods entering and leaving the warehouse can be improved, and the time and cost of picking up goods can be reduced; the goods can be stored and retrieved in the order of first-in-first-out, and the quality and effectiveness of the goods can be guaranteed; the automation and intelligence of the warehouse can be realized, and human intervention and errors can be reduced.

[0144] In addition, the warehouse management strategy is determined through the above process, which can be determined according to the storage situation of the logistics warehouse at the corresponding moment. In actual applications, the goods stored in the logistics warehouse are dynamically changing. The first warehouse storage cost and the first dead material balance corresponding to the logistics warehouse at the current moment and the second warehouse storage cost and the second dead material balance corresponding to the target moment can be obtained, and then the first warehouse storage cost is compared with the second warehouse storage cost, and the first dead material balance is compared with the second dead material balance. If the second dead material balance is greater than or equal to the first dead material balance, and / or the second warehouse storage cost is greater than the first warehouse storage cost, parameter adjustment information for the linear programming model is obtained, and the target parameters in the linear programming model are adjusted according to the parameter adjustment information to obtain a new linear programming model. Therefore, when the data of the logistics warehouse changes, the linear programming model can be re-run and the parameters of the linear programming model can be adjusted according to the feedback from actual operations to continuously optimize the warehouse management, realize dynamic management of the logistics warehouse, continuously improve the utilization rate of warehouse storage space, and reduce cargo accumulation.

[0145] Among them, the target time is the time point when the warehouse management strategy is executed for a preset time, the parameter adjustment information is the information for adjusting the parameters related to the cost information in the linear programming model, and the surplus of obsolete materials can be the goods that have been stored in the warehouse for a long time and have not been shipped out or used in time.

[0146] It should be noted that the embodiments of the present invention include but are not limited to the above examples. It is understandable that those skilled in the art can also make settings according to actual needs under the guidance of the ideas of the embodiments of the present invention, and the present invention is not limited to this.

[0147] In an embodiment of the present invention, in the process of managing a logistics warehouse, for the goods currently stored in the logistics warehouse, the warehouse information of the logistics warehouse at the current moment can be obtained, and then a linear programming model for the logistics warehouse and constraints for the linear programming model are obtained, and the warehouse information is processed according to the linear programming model and the constraints to obtain a warehouse management strategy for the logistics warehouse, and then the warehouse layout and outbound operation process of the logistics warehouse are adjusted according to the warehouse management strategy, so as to optimize the storage plan of the warehouse by introducing a linear programming method, so as to improve the utilization rate of the warehouse storage space and reduce the accumulation of goods. At the same time, adjusting the outbound operation process can improve the efficiency of goods in and out of the warehouse, reduce the time and cost of picking up goods, and realize warehouse automation and intelligence, and reduce human intervention and errors.

[0148] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the following examples are used for exemplary description:

[0149] Reference Figure 2 , shows a schematic diagram of the management process of a logistics warehouse provided in an embodiment of the present invention, and the specific process may include:

[0150] 1. Collect cargo information, warehouse location information, cost information, etc.;

[0151] 2. Construct a linear programming model for warehouse storage;

[0152] 3. Set storage constraints, cargo constraints, and first-in-first-out constraints;

[0153] 4. Enter the information collected in the first step into the warehouse storage linear programming model to calculate the optimal storage plan;

[0154] 5. Adjust warehouse layout and operation process based on the optimal storage solution to verify whether the expected effect is achieved;

[0155] 6. Regularly update warehouse data, adjust models and parameters, and continuously optimize warehouse storage linear programming models.

[0156] By introducing the linear programming method, we can optimize the warehouse storage plan under the premise of meeting the first-in-first-out principle, improve the utilization rate of warehouse storage space, and reduce the accumulation of goods; improve the efficiency of goods in and out of the warehouse, reduce the time and cost of picking up goods; ensure that goods are stored and retrieved in the order of first-in-first-out, and ensure the quality and effectiveness of goods; realize warehouse automation and intelligence, and reduce human intervention and errors.

[0157] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0158] Reference Figure 3 , shows a structural block diagram of a logistics warehouse management device provided in an embodiment of the present invention, which may specifically include the following modules:

[0159] The data acquisition module 301 is used to obtain the warehouse information of the logistics warehouse at the current moment;

[0160] A model determination module 302 is used to obtain a linear programming model for the logistics warehouse and constraints for the linear programming model, process the warehouse information according to the linear programming model and the constraints, and obtain a warehouse management strategy for the logistics warehouse;

[0161] The adjustment module 303 is used to adjust the warehouse layout and outbound operation process of the logistics warehouse according to the warehouse management strategy.

[0162] In some feasible implementations, the constraint conditions at least include storage constraint conditions, cargo constraint conditions, and first-in-first-out constraint conditions. The storage constraint conditions represent that one cargo is stored in the same storage location in the logistics warehouse. The cargo constraint conditions represent that each cargo is stored in only one location. The first-in-first-out constraint conditions represent that the cargo first stored in the logistics warehouse is taken out first. The model determination module 302 is specifically used for:

[0163] The warehouse information is processed according to the linear programming model, the storage constraint condition, the cargo constraint condition and the first-in-first-out constraint condition to obtain a warehouse management strategy for the logistics warehouse.

[0164] In some feasible implementations, the warehouse information includes at least cargo information, location information, and cost information, and the model determination module 302 is specifically used to:

[0165] The cargo information, the location information and the cost information are input into the linear programming model for solving, and are constrained according to the storage constraints, the cargo constraints and the first-in-first-out constraints, and a warehouse management strategy for the logistics warehouse is output.

[0166] In some feasible implementations, the cargo information includes at least one of cargo batch, cargo entry time, cargo volume, cargo weight, cargo name and cargo number; the location information includes at least one of the orientation, size and distance from the entrance and exit corresponding to each storage location in the logistics warehouse; the cost information includes at least one of the storage cost, pickup cost and management cost of the goods.

[0167] In some feasible implementations, the model determination module 302 is specifically used to:

[0168] Obtaining a decision variable, wherein the decision variable represents a storage state of the cargo at a target location;

[0169] An objective function for the decision variables is constructed, and the objective function is used as a linear programming model for the logistics warehouse. The objective function is used to characterize the total operating cost of the logistics warehouse.

[0170] In some feasible implementations, the objective function is:

[0171] min(Z)=sum(i)*sum(j)*(C(ij)*cdotG(ij))+sum(i)*sum(j)*(D(ij)*cdotW(ij));

[0172] Wherein, C(ij) is the unit storage cost of goods i stored at location j;

[0173] D(ij) is the unit cost of taking out the item i from the location j;

[0174] W(ij) is the state variable when the item i is taken out from the position j;

[0175] The sum(i)*sum(j)*(C(ij)*cdotG(ij)) is the total storage cost corresponding to the goods stored at each location;

[0176] The sum(i)*sum(j)*(D(ij)*cdotW(ij)) is the total cost of taking each item out from the storage location;

[0177] The min(Z) is the total operating cost.

[0178] In some feasible implementations, the warehouse management strategy includes at least the storage location and pickup order corresponding to each cargo, and the adjustment module 303 is specifically used to:

[0179] The storage position of the goods in the logistics warehouse is adjusted according to the storage position, and the goods are picked up according to the picking order, where the picking order represents that the goods that enter the logistics warehouse first are taken out first.

[0180] Some possible implementations also include:

[0181] An information acquisition module, used to acquire the first warehouse storage cost and the first surplus stock of the logistics warehouse corresponding to the current moment and the second warehouse storage cost and the second surplus stock of the logistics warehouse corresponding to the target moment;

[0182] A model adjustment module 303 is used to obtain parameter adjustment information for the linear programming model if the second surplus stock is greater than or equal to the first surplus stock, and / or the second warehouse storage cost is greater than the first warehouse storage cost, and adjust the target parameters in the linear programming model according to the parameter adjustment information to obtain a new linear programming model;

[0183] The target time is the time point when the warehouse management strategy is executed for a preset time, and the parameter adjustment information is the information for adjusting the parameters related to the cost information in the linear programming model.

[0184] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0185] In addition, an embodiment of the present invention further provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned logistics warehouse management method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0186] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, each process of the above-mentioned logistics warehouse management method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0187] Figure 4 A schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0188] The electronic device 400 includes but is not limited to: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, a processor 410, and a power supply 411. Those skilled in the art will appreciate that the electronic device structure involved in the embodiments of the present invention does not constitute a limitation on the electronic device, and the electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently. In the embodiments of the present invention, the electronic device includes but is not limited to a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted terminal, a wearable device, and a pedometer.

[0189] It should be understood that in the embodiment of the present invention, the radio frequency unit 401 can be used for receiving and sending signals during information transmission or communication. Specifically, after receiving downlink data from the base station, it is sent to the processor 410 for processing; in addition, uplink data is sent to the base station. Generally, the radio frequency unit 401 includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. In addition, the radio frequency unit 401 can also communicate with the network and other devices through a wireless communication system.

[0190] The electronic device provides users with wireless broadband Internet access through the network module 402, such as helping users to send and receive emails, browse web pages, and access streaming media.

[0191] The audio output unit 403 can convert the audio data received by the RF unit 401 or the network module 402 or stored in the memory 409 into an audio signal and output it as sound. Moreover, the audio output unit 403 can also provide audio output related to a specific function performed by the electronic device 400 (for example, a call signal reception sound, a message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, a receiver, etc.

[0192] The input unit 404 is used to receive audio or video signals. The input unit 404 may include a graphics processor (GPU) 4041 and a microphone 4042, and the graphics processor 4041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 406. The image frame processed by the graphics processor 4041 can be stored in the memory 409 (or other storage medium) or sent via the radio frequency unit 401 or the network module 402. The microphone 4042 can receive sound and can process such sound into audio data. The processed audio data can be converted into a format output that can be sent to a mobile communication base station via the radio frequency unit 401 in the case of a telephone call mode.

[0193] The electronic device 400 also includes at least one sensor 405, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 4061 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 4061 and / or the backlight when the electronic device 400 is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), and can detect the magnitude and direction of gravity when stationary, which can be used to identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; the sensor 405 can also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be repeated here.

[0194] The display unit 406 is used to display information input by the user or information provided to the user. The display unit 406 may include a display panel 4061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0195] The user input unit 407 can be used to receive input digital or character information, and to generate key signal input related to user settings and function control of the electronic device. Specifically, the user input unit 407 includes a touch panel 4071 and other input devices 4072. The touch panel 4071, also known as a touch screen, can collect the user's touch operation on or near it (such as the user's operation on the touch panel 4071 or near the touch panel 4071 using any suitable object or accessory such as a finger, stylus, etc.). The touch panel 4071 may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the contact point coordinates, and then sends it to the processor 410, receives the command sent by the processor 410 and executes it. In addition, the touch panel 4071 can be implemented using various types such as resistive, capacitive, infrared and surface acoustic waves. In addition to the touch panel 4071, the user input unit 407 may also include other input devices 4072. Specifically, other input devices 4072 may include but are not limited to a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail here.

[0196] Further, the touch panel 4071 may be covered on the display panel 4061. When the touch panel 4071 detects a touch operation on or near it, it is transmitted to the processor 410 to determine the type of the touch event, and then the processor 410 provides a corresponding visual output on the display panel 4061 according to the type of the touch event. It can be understood that in one embodiment, the touch panel 4071 and the display panel 4061 are used as two independent components to implement the input and output functions of the electronic device, but in some embodiments, the touch panel 4071 and the display panel 4061 can be integrated to implement the input and output functions of the electronic device, which is not limited here.

[0197] The interface unit 408 is an interface for connecting an external device to the electronic device 400. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, etc. The interface unit 408 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic device 400 or may be used to transmit data between the electronic device 400 and an external device.

[0198] The memory 409 can be used to store software programs and various data. The memory 409 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory 409 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0199] The processor 410 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 409, and calling data stored in the memory 409, so as to monitor the electronic device as a whole. The processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 410.

[0200] The electronic device 400 may also include a power supply 411 (such as a battery) for supplying power to each component. Preferably, the power supply 411 may be logically connected to the processor 410 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system.

[0201] In addition, the electronic device 400 includes some functional modules not shown, which will not be described in detail here.

[0202] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0203] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0204] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

[0205] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0206] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0207] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0208] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0209] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0210] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0211] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A logistics warehouse management method, characterized in that: include: Get the current warehouse information of the logistics warehouse; Obtaining a linear programming model for the logistics warehouse and constraints for the linear programming model, processing the warehouse information according to the linear programming model and the constraints, and obtaining a warehouse management strategy for the logistics warehouse; The warehouse layout and outbound operation process of the logistics warehouse are adjusted according to the warehouse management strategy.

2. The method according to claim 1, characterized in that The constraint conditions at least include storage constraint conditions, cargo constraint conditions and first-in-first-out constraint conditions. The storage constraint conditions indicate that one cargo is stored in the same storage location in the logistics warehouse. The cargo constraint conditions indicate that each cargo is stored in only one location. The first-in-first-out constraint conditions indicate that the cargo first stored in the logistics warehouse is taken out first. The warehouse information is processed according to the linear programming model and the constraint conditions to obtain a warehouse management strategy for the logistics warehouse, including: The warehouse information is processed according to the linear programming model, the storage constraint condition, the cargo constraint condition and the first-in-first-out constraint condition to obtain a warehouse management strategy for the logistics warehouse.

3. The method according to claim 2, characterized in that The warehouse information includes at least cargo information, location information and cost information. The warehouse information is processed according to the linear programming model, the storage constraint condition, the cargo constraint condition and the first-in-first-out constraint condition to obtain a warehouse management strategy for the logistics warehouse, including: The cargo information, the location information and the cost information are input into the linear programming model for solving, and are constrained according to the storage constraints, the cargo constraints and the first-in-first-out constraints, and a warehouse management strategy for the logistics warehouse is output.

4. The method according to claim 3, characterized in that The cargo information includes at least one of cargo batch, cargo entry time, cargo volume, cargo weight, cargo name and cargo number; the location information includes at least one of the orientation, size and distance from the entrance and exit corresponding to each storage location in the logistics warehouse; the cost information includes at least one of the storage cost, pickup cost and management cost of the cargo.

5. The method according to any one of claims 1 to 4, characterized in that: The obtaining of a linear programming model for the logistics warehouse includes: Obtaining a decision variable, wherein the decision variable represents a storage state of the cargo at a target location; An objective function for the decision variables is constructed, and the objective function is used as a linear programming model for the logistics warehouse. The objective function is used to characterize the total operating cost of the logistics warehouse.

6. The method according to claim 5, characterized in that The objective function is: min(Z)=sum(i)*sum(j)*(C(ij)*cdotG(ij))+sum(i)*sum(j)*(D(ij)*cdotW(ij)); Wherein, C(ij) is the unit storage cost of goods i stored at location j; D(ij) is the unit cost of taking out the item i from the location j; W(ij) is the state variable when the item i is taken out from the position j; The sum(i)*sum(j)*(C(ij)*cdotG(ij)) is the total storage cost corresponding to the goods stored at each location; The sum(i)*sum(j)*(D(ij)*cdotW(ij)) is the total cost of taking each item out from the storage location; The min(Z) is the total operating cost.

7. The method according to claim 1, characterized in that The warehouse management strategy at least includes the storage location and pickup order of each cargo. The warehouse layout and outbound operation process of the logistics warehouse are adjusted according to the warehouse management strategy, including: The storage position of the goods in the logistics warehouse is adjusted according to the storage position, and the goods are picked up according to the picking order, where the picking order represents that the goods that enter the logistics warehouse first are taken out first.

8. The method according to claim 1, characterized in that Also includes: Obtain the first warehouse storage cost and the first surplus stock of the logistics warehouse corresponding to the current moment and the second warehouse storage cost and the second surplus stock of the logistics warehouse corresponding to the target moment; If the second surplus stock is greater than or equal to the first surplus stock, and / or the second warehouse storage cost is greater than the first warehouse storage cost, then obtaining parameter adjustment information for the linear programming model, and adjusting the target parameters in the linear programming model according to the parameter adjustment information to obtain a new linear programming model; The target time is the time point when the warehouse management strategy is executed for a preset time, and the parameter adjustment information is the information for adjusting the parameters related to the cost information in the linear programming model.

9. A management device for a logistics warehouse, characterized in that: include: Data acquisition module, used to obtain the current warehouse information of the logistics warehouse; A model determination module, used to obtain a linear programming model for the logistics warehouse and constraints for the linear programming model, process the warehouse information according to the linear programming model and the constraints, and obtain a warehouse management strategy for the logistics warehouse; The adjustment module is used to adjust the warehouse layout and outbound operation process of the logistics warehouse according to the warehouse management strategy.

10. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to any one of claims 1 to 8 when executing the program stored in the memory.

11. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 8.

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