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

Abstract

The invention relates to a logistics warehouse warehousing management method and device, electronic equipment and a storage medium, and particularly relates to the technical field of logistics management, and the method comprises the steps: obtaining a warehousing forecast list and the storage remaining number of each warehouse, and extracting the warehousing cargo number according to the warehousing forecast list; comparing the storage remaining quantity of the warehouse with the quantity of the warehoused goods to obtain a comparison result; based on the comparison result, judging whether the accommodating quantity of each warehouse is greater than or equal to the quantity of warehoused goods; if yes, recording the warehouse as a planned warehouse; if not, carrying out batch processing on the warehousing goods recorded in the warehousing forecast list; the warehouse-in goods are distributed to a plurality of warehouses with storage conditions, the warehouses with the storage conditions are determined as warehouse-in warehouses, and the positions of the warehouse-in warehouses are different; and based on the warehouse-in goods and the warehouse-in warehouse, generating a warehouse-in plan list. The method has the effect of improving the warehousing planning rate.

Description

Technical Field

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

[0002] In modern logistics systems, warehouse inbound management is a crucial component, directly impacting logistics efficiency, cost control, and customer satisfaction. With the advancement of technology, warehouse inbound management methods are constantly evolving to adapt to growing storage demands and complex market environments.

[0003] A related logistics warehouse inbound management method that widely adopts a series of efficient, accurate, and automated methods and technologies. This includes the use of barcodes or RFID technology to quickly identify and record incoming goods, and the use of WMS (Warehouse Management System) or ERP (Enterprise Resource Planning) systems to enable real-time updating and sharing of inventory information.

[0004] However, RFID technology only records the goods entering the warehouse and does not allocate goods according to the storage situation in the warehouse, which reduces the inventory planning rate. Summary of the Invention

[0005] In order to improve the warehousing planning rate, the present application provides a logistics warehouse warehousing management method, device, electronic equipment and storage medium.

[0006] In the first aspect, the present application provides a logistics warehouse warehousing management method, which adopts the following technical solutions: Obtain the incoming goods forecast order and the remaining quantity in each warehouse, and extract the incoming goods quantity according to the incoming goods forecast order; Comparing the remaining quantity stored in each warehouse with the quantity of incoming goods to obtain a comparison result; Based on the comparison results, determine whether the quantity that can be accommodated in each warehouse is greater than or equal to the quantity of incoming goods; If not, the incoming goods recorded in the incoming advance order are processed in batches; the incoming goods are distributed to multiple incoming warehouses, which are warehouses with storage conditions and are located in different locations; Based on the incoming goods and the incoming warehouse, an incoming plan is generated.

[0007] By adopting the above technical solution, when faced with goods incoming warehousing planning, the system first obtains the incoming warehousing forecast and the remaining storage quantity information of each warehouse, and then accurately extracts the quantity of goods that need to be incoming. By comparing the remaining storage quantity of the warehouse with the number of incoming goods, an accurate comparison result can be obtained. Based on the comparison result, the electronic device can intelligently determine whether the capacity of each warehouse is sufficient to accommodate the incoming goods. For warehouses that can accommodate incoming goods, the electronic device directly records the warehouse that accommodates the incoming goods as the planned warehouse. For warehouses that cannot accommodate incoming goods, the electronic device cleverly batches the incoming goods and reasonably distributes the incoming goods to multiple warehouses with storage conditions. These warehouses with storage conditions are identified as incoming warehouses. Finally, the electronic device efficiently generates an incoming warehousing plan based on the incoming goods and the incoming warehouses. Compared with traditional manual planning methods, the technical solution significantly improves the intelligence level and processing efficiency of incoming warehousing planning, effectively reduces human errors and planning time, and thus improves the effectiveness of overall warehouse management.

[0008] In another possible implementation method, warehouses that meet the storage conditions are identified as receiving warehouses, including: Get the current maximum capacity and currently used capacity of each warehouse; Calculate the remaining capacity of each warehouse according to the current maximum capacity and the current used capacity; Comparing the remaining capacity with a preset capacity threshold, and if the remaining capacity is greater than or equal to the preset capacity threshold, determining the warehouse with the remaining capacity greater than or equal to the preset capacity threshold as a selectable warehouse, where the preset capacity threshold is a percentage of the quantity of the incoming goods; Obtain the storage period of incoming goods; Determining a target warehouse based on the selectable warehouses and the storage period, wherein the target warehouse is a warehouse among the selectable warehouses whose storage period is longer than the storage period of the incoming goods; Obtaining the transportation speed of the transportation tool and the location of the target warehouse; The receiving warehouse is determined based on the transportation speed and the location of the target warehouse.

[0009] By adopting the above technical solution, when determining incoming warehouses, the current maximum capacity and currently used capacity of each warehouse are obtained, thereby accurately calculating the remaining capacity of each warehouse. The remaining capacity of each warehouse is compared with a preset capacity threshold, which is set as a percentage of the number of incoming goods to ensure that the warehouse has sufficient space to accommodate the incoming goods. If the remaining capacity of a warehouse is greater than and / or equal to the preset capacity threshold, the warehouse is marked as a selectable warehouse. Furthermore, the storage period of the incoming goods is obtained, and combined with the information of the selectable warehouses, warehouses with storage periods longer than the storage period of the incoming goods are screened out. This screening of warehouses with storage periods longer than the storage period of the incoming goods accurately identifies warehouses that can accommodate the incoming goods. Warehouses with storage periods longer than the storage period of the incoming goods are selected as target warehouses, ensuring that the storage time of the goods in the warehouse does not exceed the shelf life of the goods. In addition, the transportation speed of the transportation vehicle and the location of the target warehouse are taken into consideration to ultimately determine an incoming warehouse with fast and convenient transportation. This not only improves the accuracy of incoming warehouse selection but also takes into account the storage period and transportation costs of the goods, thereby improving warehouse management and reducing economic losses caused by improper storage. Compared with the traditional warehouse selection method, it can improve the intelligence level of warehouse management.

[0010] In another possible implementation, determining the target warehouse based on the selectable warehouses and the storage period includes: Determining the storage period of the optional warehouse and the storage period of the incoming goods; Calculating a valid difference based on the storage period of the selectable warehouse and the storage period of the incoming goods; If the effective difference is greater than the preset commodity expiration threshold, the selectable warehouse with the effective difference greater than the preset commodity expiration threshold is determined as the target warehouse. Storage period Storage period By adopting the above technical solution, in the process of determining the target warehouse, the storage period of the selectable warehouse and the storage period of the incoming goods are first accurately determined; then, based on the storage period of the selectable warehouse and the storage period of the incoming goods, the effective difference is calculated, that is, the difference between the storage period of the warehouse and the storage period of the goods; if the calculated effective difference is greater than the preset commodity expiration threshold, the warehouse is determined as the target warehouse. The calculation of the effective difference can ensure that the selectable warehouse not only has sufficient storage space, but also meets the storage period requirements of the goods, thereby avoiding the risk of goods expiring in the warehouse and significantly improving the accuracy of warehouse selection.

[0011] In another possible implementation, determining the receiving warehouse based on the transportation speed and the location of the target warehouse includes: Obtaining the transportation distance from the transportation tool to the target warehouse and the congestion situation of the transportation tool to the target warehouse; generating at least one warehouse combination according to the remaining quantity stored in the warehouse and the number of incoming goods, wherein the warehouse combination is a combination of target warehouses that can accommodate the number of incoming goods; Calculating a comprehensive score for each warehouse combination, where the comprehensive score is a weighted sum of the remaining storage quantity, the transportation distance, and the congestion situation in each warehouse combination; The comprehensive scores of each warehouse combination are sorted, the warehouse combination with the highest comprehensive score is selected, and the target warehouse in the warehouse combination with the highest comprehensive score is determined as the receiving warehouse.

[0012] By employing this technical solution, the transport distance from the transport vehicle to the target warehouse and the congestion status of the route are captured during the process of determining the incoming warehouse. This provides an important reference for subsequent calculations. Based on the remaining warehouse capacity and the number of incoming goods, at least one warehouse combination is generated, each capable of accommodating the current number of goods to be received. Each warehouse combination is then comprehensively evaluated to calculate a score. The score is a weighted sum of the remaining warehouse capacity, transport distance, and congestion status, taking into account factors such as storage space, transportation efficiency, and traffic conditions. The comprehensive scores of all warehouse combinations are ranked, and the combination with the highest score is selected as the target warehouse within this combination, which is then determined as the final incoming warehouse. This ensures that the selected incoming warehouse meets storage needs while improving transportation efficiency, thereby increasing incoming warehouse efficiency.

[0013] In another possible implementation, after determining the receiving warehouse based on the transportation speed and the location of the target warehouse, the method further includes: Traversing the usage of the incoming warehouse in the current time period, the usage status is normal use and unusable, and the unusable status is that the incoming warehouse is damaged or the incoming warehouse is under maintenance; When the usage status is unusable, the remaining available capacity and migration capacity of each alternative warehouse are obtained. The migration capacity is the cargo capacity of the incoming warehouse with the usage status unusable, and the alternative warehouse is the warehouse with the usage status of the incoming warehouse in normal use; Obtaining the candidate warehouse load of each candidate warehouse within a preset historical time period; Based on the migration capacity and the load of the alternative warehouse, the expansion amount of the expansion warehouse is determined, and the expansion warehouse is a warehouse that stores the migration capacity and the load of the alternative warehouse. By implementing this technical solution, the electronic device continues to operate after successfully placing incoming goods into the incoming warehouse. Instead, it monitors and manages warehouse usage. The electronic device reviews incoming warehouse usage during the current time period, accurately determining whether the incoming warehouse is in normal use or unavailable. If an incoming warehouse is found to be unavailable, the electronic device immediately activates an emergency response mechanism, obtaining the remaining available capacity and relocation capacity of all alternative warehouses. The electronic device also obtains load data for each alternative warehouse over a preset historical time period to gain a more comprehensive understanding of the operational status and capacity of each incoming warehouse. This data is then further analyzed to determine the appropriate expansion capacity for the warehouse. This ensures that goods are properly stored and prevents losses caused by warehouse unavailability. This enables rapid and accurate response to emergencies such as warehouse unavailability, effectively ensuring smooth logistics operations.

[0014] In another possible implementation, determining the expansion amount of the expanded warehouse based on the migration capacity and the load of the candidate warehouse includes: If the load of the candidate warehouse is greater than or equal to the preset load threshold, then the slope of the load factor curve of the candidate warehouse in the preset historical time period is calculated; Calculating the storage demand growth of the candidate warehouse based on the slope of the load factor curve; An expansion amount of the expansion warehouse is calculated based on the migration capacity, the storage demand growth amount and the remaining available capacity.

[0015] By adopting the above technical solution, when determining the expansion amount of the expanded warehouse, the load of the alternative warehouse will be judged first. If the load of the alternative warehouse is greater than or equal to the preset load threshold, the electronic device will further analyze the slope of the load factor curve of the warehouse within the preset historical time period; the slope of the load factor curve reflects the trend of changes in the warehouse load over time, and the future storage demand growth of the alternative warehouse can be predicted through calculation. By comprehensively considering the migration capacity, the growth of storage demand and the remaining available capacity of the alternative warehouse, the expansion amount required to expand the warehouse can be accurately calculated. This makes it possible to dynamically adjust the warehouse capacity to deal with emergencies such as the warehouse being unavailable. Compared with the traditional static management method, it can significantly improve the intelligence level of warehouse management, while reducing the risk of logistics interruption caused by warehouse problems.

[0016] In another possible implementation, the method further includes: Get the purchase quantity of each warehouse in the historical time period; Determine a cargo flow curve based on the incoming cargo volume of each warehouse during the historical time period; Based on the cargo flow curve, predict the average daily cargo volume of each warehouse in the next time period; If the total daily average purchase volume of each warehouse in the next time period exceeds the preset remaining storage threshold, a capacity expansion warning is triggered.

[0017] By adopting the above technical solution, warehouse management collects incoming goods data for each warehouse over a historical period and plots a cargo flow curve based on this data. This cargo flow curve visually illustrates the changing trends in warehouse incoming goods, helping managers understand warehouse operations. Using the cargo flow curve, the electronic device predicts the average daily incoming goods volume for each warehouse for the next period. The sum of the predicted average daily incoming goods volume for each warehouse for the next period is compared with a preset remaining storage threshold. If the sum exceeds the preset remaining storage threshold, indicating that the warehouse's storage capacity may not be able to meet future incoming goods demand, the electronic device triggers a capacity expansion warning, prompting managers to take timely measures, such as increasing warehouse capacity or optimizing cargo storage methods, to avoid the risk of warehouse overload. Through data analysis and prediction, intelligent warehouse management and early warning are achieved. This not only enables early detection of potential storage capacity shortages, but also provides prompt alerts to managers.

[0018] In a second aspect, the present application provides a logistics warehouse warehousing management method and device, which adopts the following technical solution: A logistics warehouse warehousing management device, comprising: An information acquisition module is used to obtain the incoming goods forecast order and the remaining quantity stored in each warehouse, and extract the quantity of incoming goods based on the incoming goods forecast order; An information comparison module is used to compare the remaining quantity stored in each warehouse with the quantity of the incoming goods to obtain a comparison result; An information judgment module is used to judge whether the quantity that can be accommodated by each warehouse is greater than or equal to the quantity of incoming goods based on the comparison result; The goods allocation module is used to, if not, batch process the incoming goods recorded in the incoming advance order; allocate the incoming goods to multiple incoming warehouses, which are warehouses with storage conditions and are located in different locations; A generation module is used to generate a warehousing plan based on the goods that need to be warehousing in batches and the warehousing warehouse.

[0019] By adopting the above technical solution, when planning the incoming goods, the information acquisition module first obtains the incoming goods forecast and the remaining storage quantity information of each warehouse, and then accurately extracts the quantity of goods that need to be stored. The information comparison module compares the remaining storage quantity of the warehouse with the number of incoming goods to obtain an accurate comparison result. The information judgment module can intelligently determine whether the capacity of each warehouse is sufficient to accommodate the incoming goods based on the comparison results. For warehouses that can accommodate incoming goods, the cargo allocation module directly records the warehouse that can accommodate incoming goods as the planned warehouse. For warehouses that cannot accommodate incoming goods, the cargo allocation module cleverly batches the incoming goods and reasonably allocates them to multiple warehouses with storage conditions. These warehouses with storage conditions are identified as incoming warehouses. Finally, the generation module efficiently generates an incoming goods plan based on the incoming goods and incoming warehouses. Compared with traditional manual planning methods, this technical solution significantly improves the intelligence level and processing efficiency of incoming goods planning, effectively reduces human errors and planning time, and thus improves the efficiency of overall warehouse management.

[0020] In another possible implementation, when determining a warehouse that meets the storage conditions as an incoming warehouse, the goods allocation module is specifically configured to: Get the current maximum capacity and currently used capacity of each warehouse; Calculate the remaining capacity of each warehouse according to the current maximum capacity and the current used capacity; Comparing the remaining capacity with a preset capacity threshold, and if the remaining capacity is greater than or equal to the preset capacity threshold, determining the warehouse with the remaining capacity greater than or equal to the preset capacity threshold as a selectable warehouse, where the preset capacity threshold is a percentage of the quantity of the incoming goods; Obtain the storage period of incoming goods; Determining a target warehouse based on the selectable warehouses and the storage period, wherein the target warehouse is a warehouse among the selectable warehouses whose storage period is longer than the storage period of the incoming goods; Obtaining the transportation speed of the transportation tool and the location of the target warehouse; The receiving warehouse is determined based on the transportation speed and the location of the target warehouse.

[0021] In another possible implementation, when determining the target warehouse based on the selectable warehouses and the storage period, the cargo allocation module is specifically configured to: Determining the storage period of the optional warehouse and the storage period of the incoming goods; Calculating a valid difference based on the storage period of the selectable warehouse and the storage period of the incoming goods; If the effective difference is greater than the preset commodity expiration threshold, it is determined as the target warehouse.

[0022] In another possible implementation, when determining the incoming warehouse based on the transport speed and the location of the target warehouse, the cargo allocation module is specifically configured to: Obtaining the transportation distance from the transportation tool to the target warehouse and the congestion situation of the transportation tool to the target warehouse; generating at least one warehouse combination according to the remaining quantity stored in the warehouse and the number of incoming goods, wherein the warehouse combination is a combination of target warehouses that can accommodate the number of incoming goods; Calculating a comprehensive score for each warehouse combination, where the comprehensive score is a weighted sum of the remaining storage quantity, the transportation distance, and the congestion situation in each warehouse combination; The comprehensive scores of each warehouse combination are sorted, the warehouse combination with the highest comprehensive score is selected, and the target warehouse in the warehouse combination with the highest comprehensive score is determined as the receiving warehouse.

[0023] In another possible implementation, after determining the receiving warehouse based on the transportation speed and the location of the target warehouse, the device further includes: A traversal module is used to traverse the usage of the incoming warehouse in the current time period, where the usage status includes normal use and unusable use, and the unusable condition is that the incoming warehouse is damaged or under maintenance; A capacity acquisition module is configured to acquire the remaining available capacity and migration capacity of each alternative warehouse when the usage status is unusable, wherein the migration capacity is the cargo capacity of the incoming warehouse whose usage status is unusable, and the alternative warehouse is the warehouse whose usage status of the incoming warehouse is normally used; A load acquisition module is used to obtain the load of each candidate warehouse within a preset historical time period; The expansion amount determination module is used to determine the expansion amount of the expansion warehouse based on the migration capacity and the load of the alternative warehouse. The expansion warehouse is a warehouse that stores the migration capacity and the load of the alternative warehouse.

[0024] In another possible implementation, when the expansion amount determination module determines the expansion amount of the expanded warehouse based on the migration capacity and the load of the candidate warehouse, it is specifically configured to: If the load of the candidate warehouse is greater than or equal to the preset load threshold, then the slope of the load factor curve of the candidate warehouse in the preset historical time period is calculated; Calculating the storage demand growth of the candidate warehouse based on the slope of the load factor curve; An expansion amount of the expansion warehouse is calculated based on the migration capacity, the storage demand growth amount and the remaining available capacity.

[0025] In another possible implementation, the device further includes: The purchase quantity acquisition module is used to obtain the purchase quantity of each warehouse in the historical time period; a curve determination module, configured to determine a cargo flow curve based on the cargo volume of each warehouse during the historical time period; A forecasting module, configured to forecast the average daily cargo volume of each warehouse in the next time period based on the cargo flow curve; The early warning module is used to trigger a capacity expansion warning if the total daily average purchase volume of each warehouse in the next time period exceeds a preset remaining storage threshold.

[0026] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and at least one is configured to: execute a logistics warehouse warehousing management method shown in any possible implementation of the first aspect.

[0027] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium, when the computer program is executed in a computer, causes the computer to execute a logistics warehouse warehousing management method as described in any one of the first aspects.

[0028] In summary, this application includes at least one of the following beneficial technical effects: 1. When planning incoming goods, the system first obtains incoming goods forecasts and information on the remaining storage quantities at each warehouse, accurately determining the quantity of goods to be received. By comparing the remaining storage quantities at the warehouses with the incoming goods, an accurate comparison result can be obtained. Based on this comparison, the electronic device intelligently determines whether each warehouse has sufficient capacity to accommodate the incoming goods. For warehouses that can accommodate incoming goods, the electronic device directly records the warehouse that accommodates the incoming goods as the planned warehouse. For warehouses that cannot accommodate incoming goods, the electronic device cleverly batches the incoming goods and distributes them to multiple warehouses that meet the storage requirements. These warehouses are designated as incoming warehouses. Finally, the electronic device efficiently generates an incoming goods plan based on the incoming goods and incoming warehouses. Compared to traditional manual planning methods, this technical solution significantly improves the intelligence and efficiency of incoming goods planning, effectively reducing human errors and planning time, thereby improving the effectiveness of overall warehouse management.

[0029] 2. After successfully placing incoming goods into the incoming warehouse, the electronic device continues to monitor and manage warehouse usage. The electronic device reviews the incoming warehouse's usage during the current time period, accurately determining whether the incoming warehouse is in normal use or unavailable. If an incoming warehouse is identified as unavailable, the electronic device immediately activates an emergency response mechanism, obtaining the remaining available capacity and relocation capacity of all alternative warehouses. The electronic device also collects load data for each alternative warehouse over a preset historical time period to gain a more comprehensive understanding of the operational status and capacity of each incoming warehouse. This data is then further analyzed to determine the appropriate expansion capacity for the warehouse. This ensures that goods are properly stored and prevents loss due to warehouse unavailability. This enables quick and accurate response to emergencies such as warehouse unavailability, effectively ensuring smooth logistics operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a flow chart of a logistics warehouse warehousing management method in an embodiment of the present application.

[0031] Figure 2 It is a flow chart of a logistics warehouse warehousing management device in an embodiment of the present application.

[0032] Figure 3 It is a structural diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following is combined with Figure 1-3 This application is described in further detail.

[0034] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0035] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0036] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0037] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0038] The embodiment of the present application provides a logistics warehouse warehousing management method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, tablet computer, laptop computer, desktop computer, etc., but is not limited to this. The terminal device and the server can be directly or indirectly connected through wired or wireless communication. The embodiment of the present application does not limit this. Figure 1 As shown, the method includes: step S101, step S102, step S103, step S104, step S105, wherein, Step S101: Obtain the incoming goods forecast order and the remaining quantity stored in each warehouse, and extract the incoming goods quantity according to the incoming goods forecast order.

[0039] In an embodiment of the present application, the incoming forecast order can be obtained in real time or at a scheduled time by docking data with an enterprise resource planning (ERP) system, a supply chain management system (SCM) or other business systems. The warehouse storage remaining quantity can directly read the current storage remaining quantity of each warehouse from the warehouse management system (WMS), or obtain real-time data by calling the API interface provided by the WMS. The incoming goods quantity performs data parsing on the incoming forecast order, extracts the fields related to the incoming goods quantity, and performs data cleaning and verification to ensure that the extracted data is accurate. The present application integrates the scattered incoming forecast orders and warehouse storage remaining quantity data to provide a unified data source for subsequent steps. By extracting the incoming goods quantity, managers can clearly understand the scale of goods that will be put into storage, providing a basis for warehouse capacity planning.

[0040] Step S102: Compare the remaining quantity stored in each warehouse with the quantity of goods entering the warehouse to obtain a comparison result.

[0041] In an embodiment of the present application, the remaining storage quantity of each warehouse is compared one by one with the quantity of goods in the incoming goods forecast. The comparison results are recorded. Through this comparison, it is possible to quickly identify which warehouses can directly accommodate incoming goods and which warehouses cannot directly accommodate incoming goods and need to adopt a batch combination method to accommodate goods. This can detect insufficient warehouse capacity in advance and avoid backlogs and damage caused by the inability to enter the warehouse in time after arrival. Therefore, based on the comparison results, warehouse resources can be reasonably allocated to improve warehouse utilization.

[0042] Step S103: Based on the comparison result, determine whether the quantity that each warehouse can accommodate is greater than or equal to the quantity of incoming goods; if so, record the warehouse whose quantity that can accommodate is greater than or equal to the quantity of incoming goods as a planned warehouse.

[0043] In this embodiment of the present application, the remaining storage quantity of each warehouse is checked to see if it is greater than or equal to the number of goods entering the warehouse. For warehouses that meet the conditions, they are marked as planned warehouses and relevant information is recorded. By marking the planned warehouses, clear guidance is provided for subsequent warehousing work, ensuring that the goods can be smoothly entered into the warehouse according to plan.

[0044] If not, step S104, the incoming goods recorded in the incoming advance order are batched and distributed to multiple incoming warehouses. The incoming warehouses are warehouses that meet the storage requirements and are located in different locations. In other words, the incoming warehouses are not in the same city, or in different regions or locations within a city.

[0045] In the embodiments of the present application, for warehouses with insufficient remaining storage capacity, a batch entry plan is developed based on the number of incoming goods and the remaining warehouse capacity. The batch plan should take into account factors such as the nature and shelf life of the goods. Through batch processing and warehouse allocation, it is possible to ensure that goods can be entered into the warehouse in a timely manner. Furthermore, by selecting the appropriate location for the incoming warehouse, transportation route costs can be reduced. Among them, a warehouse with storage conditions is a warehouse that can accommodate goods.

[0046] Step S105: Generate a stocking plan based on the incoming goods and the incoming warehouse In this embodiment of the present application, the cargo information, planned warehouse information, batch loading plan, and other data in the loading forecast are integrated. Based on the integrated data, a loading plan is generated. The loading plan should include information such as the cargo name, quantity, expected arrival time, loading warehouse name, loading time, and operator. By generating a loading plan, the information of the incoming cargo can be improved, thereby improving management efficiency.

[0047] A possible implementation of the embodiment of the present application is to determine a warehouse that meets the storage conditions as an incoming warehouse, including: Get the current maximum capacity and currently used capacity of each warehouse; Calculate the remaining capacity of each warehouse according to the current maximum capacity and the current used capacity; Comparing the remaining capacity with a preset capacity threshold, and if the remaining capacity is greater than or equal to the preset capacity threshold, determining the warehouse with the remaining capacity greater than or equal to the preset capacity threshold as a selectable warehouse, where the preset capacity threshold is a percentage of the quantity of the incoming goods; Obtain the storage period of incoming goods; Determining a target warehouse based on the selectable warehouses and the storage period, wherein the target warehouse is a warehouse among the selectable warehouses whose storage period is longer than the storage period of the incoming goods; Obtaining the transportation speed of the transportation tool and the location of the target warehouse; Based on the transport speed and the location of the target warehouse, the incoming warehouse is determined. In this embodiment of the present application, the current maximum capacity and currently used capacity of each warehouse are obtained from a warehouse management system (WMS) or related data source. The remaining capacity of each warehouse is calculated using the formula: remaining capacity = current maximum capacity - current used capacity. If the remaining capacity of a warehouse is greater than or equal to a preset capacity threshold, the warehouse is marked as an available warehouse. The storage period of the incoming goods is obtained from the incoming goods forecast or cargo instructions.

[0048] By calculating the remaining capacity of warehouses and selecting warehouses that meet a preset capacity threshold, we can ensure that warehouses are fully utilized. When selecting a warehouse, we consider the storage period of the goods and ensure that the warehouse's storage period is greater than the storage period of the goods to ensure that the warehouse has the conditions to store the goods. At the same time, by considering the transportation speed of the transportation vehicle and the location of the target warehouse, we can select the warehouse with the shortest transportation time or lowest cost as the incoming warehouse, thereby improving transportation efficiency and reducing transportation costs.

[0049] Assume that there are 1,000 incoming goods, and the preset capacity threshold is 10% of the incoming goods (1000 x 10%) = 100 pieces. The storage period for the incoming goods is 60 days. Warehouse A has a remaining capacity of 150 pieces, Warehouse B has a remaining capacity of 120 pieces, Warehouse C has a remaining capacity of 90 pieces, and Warehouse D has a remaining capacity of 200 pieces. If the remaining capacity of Warehouses A, B, and D exceeds the preset capacity threshold, then Warehouses A, B, and D are eligible. The storage periods for the eligible warehouses are: Warehouse A: 90 days, Warehouse B: 70 days, and Warehouse D: 80 days. If the storage period for the incoming goods is 15 days, then Warehouses A, B, and D all have a remaining capacity greater than the incoming goods' storage period. Therefore, Warehouses A, B, and C are all target warehouses.

[0050] A possible implementation of the embodiment of the present application is to determine a target warehouse based on selectable warehouses and storage periods, including: Determine the storage period of the available warehouses and the storage period of incoming goods; Calculate the effective difference based on the storage period of the optional warehouse and the storage period of the incoming goods; If the effective difference is greater than the preset commodity expiration threshold, it will be determined as the target warehouse.

[0051] In this embodiment of the present application, the storage conditions of each selectable warehouse are obtained from the warehouse management system (WMS). By analyzing the warehouse's historical storage data, the actual shelf life of goods under different storage conditions can be understood. This is achieved by querying the warehouse's inbound and outbound records and goods status change records. The shelf life information of goods is obtained from the incoming goods forecast. The shelf life information of goods is provided by the goods manufacturer or supplier and serves as a reference for goods entering the warehouse.

[0052] The formula for calculating the effective difference is: Effective difference = Storage period of the selected warehouse - Storage period of the incoming goods. The preset product expiration threshold indicates that the goods have sufficient additional storage time in the warehouse.

[0053] Take the optional warehouse storage period as an example: Warehouse A: 90 days, Warehouse B: 70 days, Warehouse D: 80 days, and the storage period of incoming goods is 15 days. Calculate the effective difference between Warehouse A, Warehouse B, and Warehouse C.

[0054] Warehouse A's effective difference is 90-15 = 75 days; Warehouse B's effective difference is 70-15 = 55 days; and Warehouse D's effective difference is 80-15 = 65 days. Assuming the preset product expiration threshold is 30 days, Warehouses A, B, and D all exceed the preset product expiration threshold and are therefore target warehouses.

[0055] A possible implementation of the embodiment of the present application is to determine the receiving warehouse based on the transportation speed and the location of the target warehouse, including: Obtain the transportation distance from the transportation tool to the target warehouse and the congestion situation of the transportation tool to the target warehouse; Generate at least one warehouse combination based on the remaining capacity of the warehouse and the quantity of incoming goods. The warehouse combination is a combination of target warehouses that can accommodate the quantity of incoming goods. Calculate a comprehensive score for each warehouse combination, which is the weighted sum of the warehouse remaining capacity, transportation distance, and congestion situation within each warehouse combination; Sort the comprehensive scores of each warehouse combination, select the warehouse combination with the highest comprehensive score, and determine the target warehouse in the warehouse combination with the highest comprehensive score as the incoming warehouse.

[0056] In the embodiment of the present application, the real-time distance between the transport vehicle and each target warehouse is obtained through a GPS device or a map API, and the traffic department API or third-party navigation platform data is called to quantify the congestion index.

[0057] For example, if there are 1,000 pieces of incoming goods, and the remaining capacity of warehouse A is 450 pieces, the remaining capacity of B is 720 pieces, and the remaining capacity of D is 300 pieces, the warehouse combination is: Combination 1: A+B (450+720=1170 pieces); Combination 2: B+D (720+300=1020 pieces); Combination 3: A+B+D (450+720+300=1470 pieces).

[0058] The comprehensive score of the warehouse combination is calculated by the formula, which is = Σ (warehouse remaining capacity weight × inverse of remaining capacity) + Σ (transportation distance weight × inverse of distance) + Σ (congestion weight × inverse of congestion index), where the remaining capacity weight is 0.5, the transportation distance weight is 0.3, and the congestion weight is 0.2.

[0059] For example, Warehouse A has a transport distance of 50 km and a congestion index of 3. Warehouse B has a transport distance of 30 km and a congestion index of 5. Warehouse D has a transport distance of 70 km and a congestion index of 2.

[0060] Combination 1: Remaining capacity score: 1 / 450 + 1 / 720 = 0.0037. Transport distance score: 1 / 50 + 1 / 30 = 0.0533. Congestion score: 1 / 3 + 1 / 5 = 0.5333.

[0061] Comprehensive score: 0.5×0.0037+0.3×0.0533+0.2×0.5333≈0.124.

[0062] Combination 2: Remaining capacity score: 1 / 720+1 / 300=0.0049.

[0063] Transport distance score: 1 / 30+1 / 70=0.0476.

[0064] Congestion score: 1 / 5+1 / 2=0.7.

[0065] Comprehensive score: 0.5×0.0049+0.3×0.0476+0.2×0.7≈0.157.

[0066] Combination 3: Remaining capacity score: 1 / 450+1 / 720+1 / 300=0.0065.

[0067] Transport distance score: 1 / 50+1 / 30+1 / 70=0.0595.

[0068] Congestion score: 1 / 3+1 / 5+1 / 2=1.0333.

[0069] Comprehensive score: 0.5×0.0065+0.3×0.0595+0.2×1.0333≈0.230.

[0070] Through comprehensive score calculation, group A+B+D has the highest comprehensive score and is the optimal warehouse combination. Therefore, A+B+D is determined as the warehouse for receiving goods.

[0071] It should be noted that the weights for warehouse remaining capacity, transportation distance, and congestion can all be configured based on specific application scenarios. The warehouse remaining capacity weight can be set based on the storage lifespan of incoming goods. Goods with higher storage lifespan requirements receive a higher weight, while goods with lower requirements receive a lower weight. This maximizes the utilization of incoming warehouses and ensures that incoming goods are placed at the correct incoming warehouse, not simply by which incoming warehouse is the right one for the incoming goods. The weight for transportation distance increases, while the weight for shorter distances decreases. Setting a transportation distance weight avoids the high transportation costs associated with choosing a large but remote warehouse. The congestion weight is set based on real-time traffic conditions, avoiding the high waiting costs associated with choosing a nearby but congested warehouse. In other words, the warehouse remaining capacity weight, transportation distance weight, and congestion weight can all be dynamically assigned to address peak and trough periods, varying cargo characteristics, and unexpected events, allowing for rapid adaptation to a company's strategic priorities at different stages, whether during cost control or time-sensitive periods.

[0072] In one possible implementation of the embodiment of the present application, after determining the receiving warehouse based on the transportation speed and the location of the target warehouse, the method further includes: Traverse the usage of the incoming warehouse in the current time period. The usage status is normal or unavailable. The unavailable status means that the incoming warehouse is damaged or under maintenance. When the usage status is unavailable, the remaining available capacity and migration capacity of each alternative warehouse are obtained. The migration capacity is the cargo capacity of the incoming warehouse with unavailable usage status, and the alternative warehouse is the warehouse with normal usage status of the incoming warehouse. Obtain the load of each candidate warehouse within a preset historical time period; Based on the migration capacity and the load of the alternative warehouse, the expansion volume of the expanded warehouse is determined. The expanded warehouse is the warehouse that houses the migration capacity and the load of the alternative warehouse.

[0073] In an embodiment of the present application, by traversing the usage of incoming warehouses during the current time period, the warehouse status can be monitored in real time, ensuring timely detection of faults and preventing damage or retention of incoming goods. When a warehouse is unavailable, the electronic device automatically selects alternative warehouses in normal use to ensure sufficient capacity to migrate the faulty warehouse and avoid loss of goods. The load data of each alternative warehouse during a preset historical time period is extracted from the database. Understanding the historical usage of alternative warehouses provides a basis for predicting future load growth.

[0074] Assume that Warehouse E is in normal use, with a capacity of 1000 pieces and a historical load of [800, 820, 850, 900, 950]. Warehouse F is in normal use, with a capacity of 1200 pieces and a historical load of [700, 720, 750, 780, 800]. Warehouse G is damaged, with a capacity of 800 pieces. Warehouses E and F are considered "normally used" warehouses. Calculating the remaining available capacity: Warehouse A: 1000 - 950 (maximum historical load) = 50 pieces. Warehouse B: 1200 - 800 (maximum historical load) = 400 pieces.

[0075] Obtain the load data of Warehouse E and Warehouse F for the past week to predict the next load volume. For example, if the next load volume of Warehouse E is 978 pieces, the required expansion volume is 978-50=928 pieces.

[0076] Warehouse F's next load is 828 pieces. Therefore, the required capacity is 828 - 400 = 428 pieces. Since the damaged warehouse G has a capacity of 800 pieces, and neither Warehouse E nor Warehouse F can handle the goods in Warehouse G, a temporary warehouse expansion is necessary. When expanding the temporary warehouse, predicting whether the warehouse can handle the next load can help identify overloaded warehouses, prevent overload risks, and ensure sufficient capacity to meet future demand.

[0077] A possible implementation of the embodiment of the present application is to determine the expansion amount of the expansion warehouse based on the migration capacity and the load of the candidate warehouse, including: If the load of the candidate warehouse is greater than or equal to the preset load threshold, the slope of the load factor curve of the candidate warehouse in the preset historical time period is calculated; Calculate the storage demand growth of the alternative warehouse based on the slope of the load factor curve; Calculate the expansion volume for the expanded warehouse based on the migration capacity, storage demand growth, and remaining available capacity.

[0078] In this embodiment, a preset load threshold is set to traverse the historical load data of each candidate warehouse and calculate its load ratio. If the load ratio is greater than or equal to the preset threshold, the capacity expansion calculation process is triggered. This allows for the identification of overloaded warehouses through comparison, preventing the risk of warehouse overload and ensuring sufficient capacity to meet future demand.

[0079] Perform linear regression analysis on the selected warehouse's historical load data to calculate the slope of the load factor curve. This slope reflects the growth trend of the warehouse's load. It quantifies the rate of warehouse load growth and provides data for predicting future storage needs. Based on the slope of the load factor curve, the warehouse's storage demand growth over a period of time is predicted. A positive slope indicates increasing load. This slope can be used to predict changes in warehouse capacity demand in advance, avoiding the cost of temporary capacity expansion.

[0080] Assume that Warehouse E has a capacity of 1,000 pieces and a historical load of [800, 820, 850, 900, 950], with a load factor exceeding the 80% threshold. Warehouse F has a capacity of 1,200 pieces and a historical load of [700, 720, 750, 780, 800], with a load factor within the threshold. Warehouse G is damaged and has a capacity of 800 pieces (needing to relocate goods). The forecast for the next three time units shows an increase in storage demand of 64 pieces. If Warehouse A has 50 pieces of available capacity remaining and 800 pieces are relocated, the required capacity expansion is 64 + 800 − 50 = 814 pieces.

[0081] In a possible implementation of the embodiment of the present application, the method further includes: Get the purchase quantity of each warehouse in the historical time period; Determine the cargo flow curve based on the incoming cargo volume of each warehouse during the historical period; Based on the cargo flow curve, predict the average daily cargo volume of each warehouse in the next time period; If the total daily average purchase volume of each warehouse in the next time period exceeds the preset remaining storage threshold, an expansion warning will be triggered.

[0082] In this embodiment of the present application, the warehouse management system (WMS) or enterprise resource planning (ERP) system is used to extract the incoming goods data for each warehouse within a specified historical time period. The data should include the date and quantity of each incoming goods.

[0083] Use a time series analysis algorithm (such as ARIMA, exponential smoothing, or Prophet) to fit historical incoming goods data to generate a cargo flow curve. The cargo flow curve reflects the changing trends and cyclical patterns of warehouse incoming goods. Taking the ARIMA model as an example, the model parameters (p, d, q) must be determined, where p is the number of autoregressive terms, d is the differencing order, and q is the number of moving average terms. The specific steps for determining the model parameters are based on existing techniques and are not detailed in this embodiment.

[0084] Through model fitting, a mathematical expression for cargo flow is derived, which is used to predict future incoming goods. Using the established cargo flow curve, the average daily incoming goods volume for each warehouse in the next time period is predicted. A specific prediction method can be to extrapolate the cargo flow curve to the predicted time period and calculate the predicted daily incoming goods volume for that time period. Alternatively, the predicted values ​​can be aggregated to obtain the average daily incoming goods volume for each warehouse. The sum of the predicted daily average incoming goods volumes for all warehouses is calculated and compared to a preset remaining storage threshold. If the sum exceeds the threshold, a capacity expansion alert is triggered via system notification, email, or text message. This prediction and early warning mechanism prevents interruptions in incoming goods due to insufficient warehouse capacity.

[0085] The above embodiment introduces a logistics warehouse entry management method from the perspective of method flow, and the following embodiment introduces a logistics warehouse entry management method device 20 from the perspective of virtual modules or virtual units. Please refer to the following embodiment for details.

[0086] The embodiment of the present application provides a logistics warehouse entry management method device 20, such as Figure 2 As shown, the logistics warehouse entry management device 20 may specifically include: A logistics warehouse entry management device 20, comprising: The information acquisition module 201 is used to obtain the incoming goods forecast order and the remaining quantity of each warehouse, and extract the incoming goods quantity according to the incoming goods forecast order; The information comparison module 202 is used to compare the remaining quantity in the warehouse with the quantity of goods entering the warehouse to obtain a comparison result; The information judgment module 203 is used to judge whether the quantity that each warehouse can accommodate is greater than or equal to the quantity of incoming goods based on the comparison result; if so, the warehouse is recorded as a planned warehouse; If not, the goods allocation module 204 processes the incoming goods recorded in the incoming advance order in batches; allocates the incoming goods to multiple incoming warehouses, which are warehouses with storage conditions and are located in different locations; The generating module 205 is used to generate a warehousing plan based on the goods that need to be warehousing in batches and the warehousing warehouses.

[0087] By adopting the above technical solution, when planning the incoming goods, the information acquisition module 201 first obtains the incoming goods forecast and the remaining storage quantity information of each warehouse, and then accurately extracts the quantity of goods that need to be entered. The information comparison module 202 compares the remaining storage quantity of the warehouse with the number of incoming goods, and can obtain an accurate comparison result. The information judgment module 203 can intelligently determine whether the capacity of each warehouse is sufficient to accommodate the incoming goods based on the comparison results. The goods allocation module 204 directly records the warehouse that can accommodate the incoming goods as the planned warehouse for warehouses that can accommodate the incoming goods. For warehouses that cannot accommodate the incoming goods, the incoming goods are cleverly batched and reasonably allocated to multiple warehouses with storage conditions. These warehouses with storage conditions are determined as incoming warehouses. Finally, the generation module 205 efficiently generates an incoming goods plan based on the incoming goods and the incoming warehouses. Compared with traditional manual planning methods, the technical solution significantly improves the intelligence level and processing efficiency of incoming goods planning, effectively reduces human errors and planning time, and thus improves the effectiveness of overall warehouse management.

[0088] In one possible implementation of the embodiment of the present application, when the goods allocation module 204 determines a warehouse that meets the storage conditions as an incoming warehouse, it is specifically configured to: Get the current maximum capacity and currently used capacity of each warehouse; Calculate the remaining capacity of each warehouse based on the current maximum capacity and the currently used capacity; Compare the remaining capacity with the preset capacity threshold. If the remaining capacity is greater than and / or equal to the preset capacity threshold, the current warehouse is determined to be an optional warehouse. The preset capacity threshold is a percentage of the number of incoming goods. Obtain the storage period of incoming goods; Based on the available warehouses and storage periods, the target warehouse is determined. The target warehouse is the warehouse with a storage period longer than the storage period of the incoming goods. Obtain the transportation speed of the transport vehicle and the location of the target warehouse; Determine the inbound warehouse based on the shipping speed and the location of the target warehouse.

[0089] In one possible implementation of the embodiment of the present application, when determining a target warehouse based on the selectable warehouses and the storage period, the cargo allocation module 204 is specifically configured to: Determine the storage period of the available warehouses and the storage period of incoming goods; Calculate the effective difference based on the storage period of the optional warehouse and the storage period of the incoming goods; If the effective difference is greater than the preset commodity expiration threshold, it will be determined as the target warehouse.

[0090] In one possible implementation of the embodiment of the present application, when determining the incoming warehouse based on the transport speed and the location of the target warehouse, the cargo allocation module 204 may specifically: Obtain the transportation distance from the transportation tool to the target warehouse and the congestion situation of the transportation tool to the target warehouse; Generate at least one warehouse combination based on the remaining capacity of the warehouse and the quantity of incoming goods. The warehouse combination is a combination of target warehouses that can accommodate the quantity of incoming goods. Calculate a comprehensive score for each warehouse combination, which is the weighted sum of the warehouse remaining capacity, transportation distance, and congestion situation within each warehouse combination; Sort the comprehensive scores of each warehouse combination, select the warehouse combination with the highest comprehensive score, and determine the target warehouse in the warehouse combination with the highest comprehensive score as the incoming warehouse.

[0091] In one possible implementation of the embodiment of the present application, after determining the receiving warehouse based on the transport speed and the location of the target warehouse, the device 20 further includes: The traversal module is used to traverse the usage of the incoming warehouse in the current time period. The usage status is normal use and unusable. The unusable status means that the incoming warehouse is damaged or under maintenance; The capacity acquisition module is used to obtain the remaining available capacity and migration capacity of each alternative warehouse when the usage status is unavailable. The migration capacity is the cargo capacity of the incoming warehouse with unavailable usage status, and the expansion warehouse is the warehouse that stores the migration capacity and the load of the alternative warehouse; A load acquisition module is used to obtain the load of each candidate warehouse within a preset historical time period; The expansion quantity determination module is used to determine the expansion quantity of the expansion warehouse based on the migration capacity and the load of the alternative warehouse. The expansion warehouse is a warehouse for placing the incoming warehouse that is in an unusable usage state.

[0092] In one possible implementation of the embodiment of the present application, the expansion amount determination module is specifically configured to: If the load of the candidate warehouse is greater than or equal to the preset load threshold, the slope of the load factor curve of the candidate warehouse in the preset historical time period is calculated; Calculate the storage demand growth of the alternative warehouse based on the slope of the load factor curve; Calculate the expansion volume for the expanded warehouse based on the migration capacity, storage demand growth, and remaining available capacity.

[0093] In a possible implementation of the embodiment of the present application, the apparatus 20 further includes: The purchase quantity acquisition module is used to obtain the purchase quantity of each warehouse in the historical time period; A curve determination module is used to determine the cargo flow curve based on the incoming cargo volume of each warehouse in a historical time period; The forecasting module is used to predict the average daily incoming goods volume of each warehouse in the next time period based on the cargo flow curve; The early warning module is used to trigger a capacity expansion warning if the total daily average purchase volume of each warehouse in the next time period exceeds the preset remaining storage threshold.

[0094] Those skilled in the art will 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.

[0095] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3The electronic device 30 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0096] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, or a combination of a DSP and a microprocessor.

[0097] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or one type of bus.

[0098] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0099] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0100] Electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. They may also include servers, etc. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0101] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0102] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0103] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A logistics warehouse warehousing management method, characterized in that: include: Obtain the incoming goods forecast order and the remaining quantity in each warehouse, and extract the incoming goods quantity according to the incoming goods forecast order; Comparing the remaining quantity stored in each warehouse with the quantity of incoming goods to obtain a comparison result; Based on the comparison results, determine whether the quantity that can be accommodated in each warehouse is greater than or equal to the quantity of incoming goods; If not, the incoming goods recorded in the said incoming advance order shall be processed in batches; Allocating the incoming goods to a plurality of incoming warehouses, wherein the incoming warehouses are warehouses with storage conditions and are located at different locations; Based on the incoming goods and the incoming warehouse, an incoming plan is generated.

2. A logistics warehouse warehousing management method according to claim 1, characterized in that: Warehouses that meet the storage conditions will be identified as incoming warehouses, including: Get the current maximum capacity and currently used capacity of each warehouse; Calculate the remaining capacity of each warehouse according to the current maximum capacity and the current used capacity; Comparing the remaining capacity with a preset capacity threshold, and if the remaining capacity is greater than or equal to the preset capacity threshold, determining the warehouse with the remaining capacity greater than or equal to the preset capacity threshold as a selectable warehouse, where the preset capacity threshold is a percentage of the quantity of the incoming goods; Obtain the storage period of incoming goods; Determining a target warehouse based on the selectable warehouses and the storage period, wherein the target warehouse is a warehouse among the selectable warehouses whose storage period is longer than the storage period of the incoming goods; Obtaining the transport speed of the transport vehicle and the location of the target warehouse; The receiving warehouse is determined based on the transportation speed and the location of the target warehouse.

3. A logistics warehouse warehousing management method according to claim 2, characterized in that: The determining of the target warehouse based on the selectable warehouses and the storage period includes: Determining the storage period of the optional warehouse and the storage period of the incoming goods; Calculating a valid difference based on the storage period of the selectable warehouse and the storage period of the incoming goods; If the effective difference is greater than the preset commodity expiration threshold, the selectable warehouse whose effective difference is greater than the preset commodity expiration threshold is determined as the target warehouse.

4. A logistics warehouse warehousing management method according to claim 3, characterized in that: Determining the receiving warehouse based on the transportation speed and the location of the target warehouse includes: Obtaining the transportation distance from the transportation tool to the target warehouse and the congestion situation of the transportation tool to the target warehouse; generating at least one warehouse combination according to the remaining quantity stored in the warehouse and the number of incoming goods, wherein the warehouse combination is a combination of target warehouses that can accommodate the number of incoming goods; Calculating a comprehensive score for each warehouse combination, where the comprehensive score is a weighted sum of the remaining storage quantity, the transportation distance, and the congestion situation in each warehouse combination; The comprehensive scores of each warehouse combination are sorted, the warehouse combination with the highest comprehensive score is selected, and the target warehouse in the warehouse combination with the highest comprehensive score is determined as the receiving warehouse.

5. A logistics warehouse warehousing management method according to claim 4, characterized in that: After determining the receiving warehouse based on the transportation speed and the location of the target warehouse, the method further includes: Traversing the usage of the incoming warehouse in the current time period, the usage status is normal use and unusable, and the unusable status is that the incoming warehouse is damaged or the incoming warehouse is under maintenance; When the usage status is unusable, the remaining available capacity and migration capacity of each alternative warehouse are obtained, where the migration capacity is the cargo capacity of the incoming warehouse with the usage status unusable, and the alternative warehouse is the warehouse with the usage status of the incoming warehouse in normal use; Obtaining the candidate warehouse load of each candidate warehouse within a preset historical time period; Based on the migration capacity and the load of the alternative warehouse, the expansion amount of the expansion warehouse is determined, and the expansion warehouse is a warehouse that stores the migration capacity and the load of the alternative warehouse.

6. A logistics warehouse warehousing management method according to claim 5, characterized in that: The determining of the expansion amount of the expanded warehouse based on the migration capacity and the load of the candidate warehouse includes: If the load of the candidate warehouse is greater than or equal to the preset load threshold, then calculating the slope of the load factor curve of the candidate warehouse within the preset historical time period; Calculating the storage demand growth of the candidate warehouse based on the slope of the load factor curve; An expansion amount of the expansion warehouse is calculated based on the migration capacity, the storage demand growth amount and the remaining available capacity.

7. A logistics warehouse warehousing management method according to claim 6, characterized in that: The method further comprises: Get the purchase quantity of each warehouse in the historical time period; Determine a cargo flow curve based on the incoming cargo volume of each warehouse during the historical time period; Based on the cargo flow curve, predict the average daily cargo volume of each warehouse in the next time period; If the total daily average purchase volume of each warehouse in the next time period exceeds the preset remaining storage threshold, a capacity expansion warning is triggered.

8. A device for managing incoming goods in a logistics warehouse, characterized in that: include: An information acquisition module is used to obtain the incoming goods forecast order and the remaining quantity stored in each warehouse, and extract the quantity of incoming goods based on the incoming goods forecast order; An information comparison module is used to compare the remaining quantity stored in each warehouse with the quantity of the incoming goods to obtain a comparison result; An information judgment module is used to judge whether the quantity that can be accommodated by each warehouse is greater than or equal to the quantity of incoming goods based on the comparison result; The goods allocation module is used to, if not, batch process the incoming goods recorded in the incoming advance order; allocate the incoming goods to multiple incoming warehouses, which are warehouses with storage conditions and are located in different locations; A generation module is used to generate a warehousing plan based on the goods that need to be warehousing in batches and the warehousing warehouse.

9. An electronic device, characterized in that: It includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and configured to be executed by the at least one processor, and the at least one application is used to execute a logistics warehouse inbound management method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the logistics warehouse warehousing management method according to any one of claims 1 to 7.

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