Automatic storage location distribution method and device based on warehouse management system, terminal and medium

Abstract

The invention discloses an automatic storage location allocation method and device based on a warehouse management system, a terminal and a medium, and the method comprises the steps: building a hierarchical mapping relation among a warehouse, a region location and a storage location, configuring a storage location set based on a material attribute, and updating a storage location occupation state in real time; after a warehousing task is received, matching a distributable storage location set according to a material type, and preferentially selecting a continuous empty storage location with the minimum physical distance from the storage location with the same stored material; when a warehouse-out request is responded, the valid period priority rule and the scattered priority rule are executed, and space adjacent storage locations are distributed for the same order; if the storage location is not emptied after unloading, the storage location is marked as a'to-be-continued 'state, and the'to-be-continued' storage location is preferentially allocated to a subsequent task until the storage location is completely emptied. According to the invention, through adjacent distribution and state optimization, the on-shelf / off-shelf time is reduced, personnel movement and equipment loss are reduced, and the operation cost is reduced; human errors are avoided, and the inventory accuracy is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of warehouse management system, and particularly relates to a warehouse management system-based automatic allocation of storage space method and device, a terminal and a medium. BACKGROUND

[0002] In the existing warehouse management system (WMS), the allocation of storage space often adopts fixed rules or manual methods, which has the following defects:

[0003] (1) Allocation problem of upper shelf: the traditional system (such as simple allocation based on RFID) randomly selects an empty storage space when warehousing, ignoring the spatial continuity, which leads to frequent movement of the upper shelf personnel, increasing the time cost (the actual data shows that the average waste time of each operation is 2-5 minutes) ;

[0004] (2) Allocation problem of lower shelf: the warehouse is discharged according to the first-in first-out (FIFO) rule, but the proximity of the storage space and the optimization of the scattered goods are not considered, which causes repeated unloading and fragmentation of the storage space (for example, part of the occupied storage space is not processed preferentially, which reduces the unloading efficiency by more than 30%) ;

[0005] (3) Overall limitation: although the existing technology realizes automatic allocation, it lacks state recording and dynamic adjustment of priority, and cannot adapt to high-frequency warehouse demand, which is particularly prominent in high-turnover warehouses (such as cold chain logistics), resulting in low efficiency and high error rate.

[0006] Therefore, it is necessary to provide a warehouse management system-based automatic allocation of storage space method, device, terminal and medium to overcome the above defects. SUMMARY

[0007] The present application aims to provide a warehouse management system-based automatic allocation of storage space method, device, terminal and medium, which aims to solve the problem of resource waste caused by random allocation in the existing warehouse management technology, and improve the warehouse space utilization and operation efficiency.

[0008] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a warehouse management system-based automatic allocation of storage space method, comprising:

[0009] Establishing a hierarchical mapping relationship among the warehouse, the area, and the storage space, configuring a set of storable storage spaces based on the material properties, and updating the storage space occupation state in real time;

[0010] After receiving the warehousing task, matching the set of allocable storage spaces according to the material type, and preferentially selecting the continuous empty storage space with the smallest physical distance from the existing storage space of the same material;

[0011] When responding to the out-of-warehouse request, the expiration date priority rule and the scattered priority rule are executed, and the space-adjacent warehouse location is allocated for the same order; wherein the expiration date priority rule is to select the warehouse location of the earliest expiration batch; the scattered priority rule is to preferentially select the partially occupied warehouse location under the condition of meeting the expiration date;

[0012] If the warehouse location is not emptied after being taken off the shelf, it is marked as a "to-be-continued" state, and the "to-be-continued" warehouse location is preferentially allocated for subsequent tasks until it is completely emptied;

[0013] The warehouse location state database is updated after each operation, which is shared and called when shelving and out-of-warehouse.

[0014] In a preferred embodiment, a hierarchical mapping relationship of the warehouse, the zone, and the warehouse location is established, and the set of storable warehouse locations based on the material attributes includes:

[0015] The heat value of each material is calculated according to a historical out-of-warehouse frequency prediction formula, and the prediction formula is as follows:

[0016] H = λ * log N d + (1-λ)N a , λ ∈ (0, 1);

[0017] In the formula, H is the heat value of the material, N d is the daily average out-of-warehouse frequency of the material, N a is the average storage days of the material, and λ is the configuration weight;

[0018] The high-frequency materials with a preset proportion of high H values are mapped to the zone closest to the exit.

[0019] In a preferred embodiment, the implementation of the minimum physical distance specifically includes:

[0020] A warehouse location network topology graph is constructed, taking the channel intersection point as a node;

[0021] Dijkstra algorithm is used to calculate the shortest path from the current operation point to the target warehouse location; the calculation method is:

[0022] min (∑e i *w i ), i is the edge between adjacent nodes, e i is the weight of edge i, w i = 1 + η * channel congestion index; η is a configuration weight with a value interval of (0, 1).

[0023] In a preferred embodiment, the execution of the expiration date priority rule and the scattered priority rule is realized through multi-objective decision, specifically including:

[0024] The comprehensive priority score P of the warehouse location is calculated based on the following formula:

[0025] T c is the current date, T min is the earliest expiration date, T max is the latest expiration date, R is the occupancy rate of the storage location in the to-be-placed location, and a and β are preset configuration weights.

[0026] The storage location with the highest P value is selected for allocation.

[0027] In a preferred embodiment, if the storage location is not emptied after being taken off the shelf, it is marked as a "to-be-continued" state, and the subsequent task is preferentially allocated to the "to-be-continued" storage location until the complete clearing step, which further includes:

[0028] When the proportion of the "to-be-continued" state storage location in a location is greater than a preset proportion threshold, the following is automatically performed: all partially occupied storage locations in the location are searched, and a storage location merging task is generated and allocated to an idle device.

[0029] In a preferred embodiment, the following steps are further included:

[0030] A real-time storage location state heat map is displayed by different colors, and a sound and / or light alarm is triggered when the storage location is overdue.

[0031] The second aspect of the present application provides an automatic storage location allocation device based on a warehouse management system, which includes:

[0032] A storage location configuration module is configured to establish a hierarchical mapping relationship among the warehouse, location, and storage location, configure a storable storage location set based on the material properties, and update the storage location occupancy state in real time.

[0033] An in-warehouse allocation module is configured to match the allocable storage location set according to the material type after receiving the in-warehouse task, and preferentially select the continuous empty storage location with the smallest physical distance from the stored storage location of the same material.

[0034] An out-of-warehouse allocation module is configured to execute the expiration priority rule and the scattered priority rule when responding to the out-of-warehouse request, and allocate the spatially adjacent storage locations for the same order; wherein the expiration priority rule is to select the storage location of the earliest expiration batch, and the scattered priority rule is to preferentially select the partially occupied storage location under the condition of meeting the expiration date.

[0035] A storage location marking module is configured to mark the storage location as a "to-be-continued" state if the storage location is not emptied after being taken off the shelf, and preferentially allocate the "to-be-continued" storage location to the subsequent task until the complete clearing.

[0036] A storage location updating module is configured to update the storage location state database after each operation, for shared calling when the material is put on the shelf and taken out of the warehouse.

[0037] The third aspect of the present application provides a terminal, which comprises a memory, a processor, and a computer program stored in the memory, and the computer program, when executed by the processor, implements each step of the method for automatically allocating a storage location based on a warehouse management system according to any one of the above embodiments.

[0038] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements each step of the method for automatically allocating a storage location based on a warehouse management system according to any one of the above embodiments.

[0039] The fifth aspect of the present application provides a computer program product, which comprises a computer program or instructions, and the computer program or instructions, when executed by a processor, implements each step of the method for automatically allocating a storage location based on a warehouse management system according to any one of the above embodiments.

[0040] The present application provides a method and device for automatically allocating a storage location based on a warehouse management system, a terminal, and a medium, which have the following advantages:

[0041] (1) Efficiency improvement: through adjacent allocation and state optimization, the time for picking up and putting down is reduced by 25%-40%, which is particularly suitable for high-frequency warehouses (such as logistics centers handling thousands of orders per day);

[0042] (2) Cost savings: personnel movement and equipment wear and tear (such as shortened forklift paths) are reduced, and the operating cost is reduced by 15%-20%;

[0043] (3) Error rate reduction: automated state tracking avoids human errors (such as incorrect storage locations), and improves inventory accuracy to more than 99%. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0045] Figure 1 The flowchart of the method for automatically allocating a storage location based on a warehouse management system provided by the present application is shown in the figure.

[0046] Figure 2 The framework diagram of the device for automatically allocating a storage location based on a warehouse management system provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0047] In order to make the purposes, technical solutions and beneficial technical effects of the present application clearer and more understandable, the present application will be further described in detail below in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described in the present specification are only for the purpose of explaining the present application and are not intended to limit the present application.

[0048] It should also be understood that the terms used in the present application specification herein are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0049] It should be further understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0050] Embodiment one

[0051] In the embodiments of the present application, a warehouse management system-based automatic allocation of storage space method is provided, which is suitable for logistics, e-commerce and manufacturing industry scenarios, optimizes shelving and unshelving operations through intelligent algorithm, and improves warehouse space utilization and operation efficiency. Unlike traditional WMS systems, the present application focuses on a dynamic priority mechanism for storage space allocation, including material-storage space mapping based on zone, space proximity optimization and state tracking, solving the resource waste problem caused by random allocation in the prior art. Among them, the warehouse management system includes two modules of shelving allocation module and unshelving allocation module, based on the warehouse hierarchical structure (warehouse>zone>storage space), realizing automation through configuration management, algorithm optimization and state feedback.

[0052] As shown in Figure 1 The warehouse management system-based automatic allocation of storage space method includes the following steps S10-S50. The serial numbers of the steps are only for the convenience of brief description and do not limit the execution order.

[0053] Step S10: Establish the hierarchical mapping relationship of warehouse, zone and storage space, configure the storable storage space set based on material attributes, and update the storage space occupation state in real time.

[0054] The system configures the mapping relationship between materials and storage spaces at the zone level (such as material A can be allocated to storage spaces X, Y and Z), which defines the material storage rules. Configuration is based on warehouse layout (such as shelf arrangement) to ensure physical proximity of storage spaces (for example, adjacent storage space codes are continuous). The system updates the occupation state in real time and supports multiple conditions (such as material type, safety stock), improves flexibility (unlike static configuration systems), and eliminates information lag.

[0055] Specifically, the step specifically comprises: calculating the thermal value of each material according to a historical outbound frequency prediction formula, the prediction formula being as follows:

[0056] H = λ * log N d + (1-λ) N a , λ ∈ (0, 1); wherein, H is the thermal value of the material, N d is the daily average outbound frequency of the material, N a is the average storage days of the material, and λ is a configuration weight, for example, λ = 0.7; the high-frequency material with a preset proportion (for example, the top 20%) of H value is mapped to the zone closest to the exit.

[0057] Step S20: After receiving the inbound task, a set of assignable storage locations is matched according to the material type, and a continuous empty storage location with the smallest physical distance to the already stored storage location of the same material is preferentially selected.

[0058] Specifically, the step comprises: constructing a storage location network topology graph, taking the channel intersection point as a node; using Dijkstra algorithm to calculate the shortest path from the current operation point to the target storage location; the calculation method is:

[0059] min (∑e i *w i ), i is the edge between adjacent nodes, e i is the weight of edge i, and w i = 1 + η * channel congestion index; η is a configuration weight with a value interval of (0, 1), for example, η = 0.3.

[0060] For example, when the material is stored, the system scans the material information, queries the zone configuration, and automatically filters the unoccupied storage locations. Adjacent or nearby storage locations are preferentially allocated (algorithm logic: calculate the distance between storage locations, select the shortest path), for example, a continuous empty storage location is allocated for a newly arrived batch of materials. This reduces the moving distance of the shelving personnel and saves time (efficiency is improved by 25% in tests). Through proximity optimization, combined with space algorithm (such as Dijkstra shortest path) and real-time occupancy data, traditional random allocation is avoided.

[0061] Step S30: In response to the outbound request, the expiration priority rule and the scattered priority rule are executed, and spatially adjacent storage locations are allocated for the same order; wherein, the expiration priority rule is to select the storage location of the earliest expired batch; the scattered priority rule is to preferentially select a partially occupied storage location under the condition of meeting the expiration condition.

[0062] Specifically, the expiration priority rule and the scattered priority rule are implemented through multi-objective decision, specifically comprising:

[0063] The comprehensive priority score P of the storage location is calculated based on the following formula: T c is the current date, Tmin T is the earliest expiration date max R is the occupancy rate of the storage location in the to-be-placed area, and a and b are preset configuration weights, for example, a = 0.6 and b = 0.4; the storage location with the highest P value is selected for allocation.

[0064] For example, when picking up, the system retrieves the inventory according to the demand (material, batch number, quantity), and applies the double-priority rule: expiration date priority (the earliest expired material is picked up first) and scattered priority (partially occupied storage locations are preferentially selected). Adjacent storage locations are preferentially allocated (such as adjacent storage locations for the same order) to facilitate bulk unloading. Therefore, through state tracking and cyclic optimization, the system records the history of the storage location (such as the number of times of picking up), dynamically adjusts the priority, and significantly improves the picking speed (the actual reduction in time is 30%).

[0065] Step S40: If the storage location is not empty after unloading, it is marked as a "to-be-used" state, and the "to-be-used" storage location is preferentially allocated in subsequent tasks until it is completely emptied.

[0066] Further, if the storage location is not empty after unloading, it is marked as a "to-be-used" state, and the "to-be-used" storage location is preferentially allocated in subsequent tasks until it is completely emptied. In the step, it further includes: when the proportion of "to-be-used" storage locations in a certain area is greater than a preset proportion threshold (for example, 30%), automatically performing: retrieving all partially occupied storage locations in the area, and generating a storage location merging task and allocating it to an idle device. It should be noted that the term "to-be-used" here only represents a usage state of the storage location, and persons skilled in the art can also use other similar terms to explain this usage state, so this term does not limit the usage state.

[0067] For example, the system has a built-in database to record the state of the storage location (such as occupied, idle, unloaded, etc.), and is updated after each operation. The allocation of unloading and loading shares state data to ensure consistency. For example, the "to-be-used" storage location after unloading is preferentially allocated in subsequent tasks until it is completely emptied, which solves the problem of storage location fragmentation and optimizes space utilization (application case: e-commerce warehouse turnover rate increased by 20%).

[0068] Step S50: Update the storage location state database after each operation for shared calling when loading and picking up.

[0069] In one embodiment, the scheme further includes the step of: displaying the storage location state heat map in real time through different colors (for example, red: occupancy > 90%, yellow: to-be-used, green: idle), and triggering sound and / or light alarms when the storage location is overdue, thereby realizing visual monitoring.

[0070] It should be noted that the method is realized by a software module and integrated into a WMS system. The flow includes: user input task → system query configuration and state → algorithm allocation bin → feedback operation instruction → update database. The whole process is automated, reduces human intervention (error rate is reduced by 15%), and supports expansion (such as adding AI prediction of bin demand).

[0071] For ease of understanding, a simulation example is provided here. Assuming that a certain e-commerce warehouse uses the present application:

[0072] Scenario setting: warehouse partition A (storing electronic products), bin arranged by shelf row (such as A1-A10). Configuration material M1 can be stored in A1-A5;

[0073] Shelving example: new M1 material 100 pieces, system queries empty bins (A2, A3 idle), preferentially allocates adjacent bins A2 and A3 (rather than random A5), and shelving personnel completes the movement at one time;

[0074] Dismounting example: M1 50 pieces of out-of-stock demand, system retrieves inventory: A2 (30 pieces, early expiration), A3 (20 pieces, partially occupied). Preferentially allocate A2 (expiration priority) and A3 (scattered priority), and mark the remaining A3 as "to be continued". Next time, directly allocate A3 to avoid additional operations.

[0075] Technical details: the algorithm uses a database (such as MySQL) to store the state, and the allocation logic is realized by pseudo code (example: if bin adjacent and unoccupied then allocate). Test data: in 1000 operations, an average of 40% time is saved.

[0076] Example two

[0077] The present application provides an automatic bin allocation device 100 based on a warehouse management system, which is used to optimize shelving and dismounting operations through intelligent algorithms, and improve warehouse space utilization and work efficiency. It should be noted that the implementation principle and specific embodiments of the automatic bin allocation device 100 based on the warehouse management system can refer to the automatic bin allocation method based on the warehouse management system described above, and the present application will not be repeated hereinafter.

[0078] As shown in Figure 2 , the automatic bin allocation device 100 based on the warehouse management system includes:

[0079] The bin configuration module 10 is used to establish a hierarchical mapping relationship of the warehouse, the partition, and the bin, configure a storable bin set based on the material attribute, and update the bin occupancy state in real time;

[0080] The warehouse-in allocation module 20 is used for matching a set of allocable warehouse positions according to the material type after receiving a warehouse-in task, and preferentially selecting a continuous empty warehouse position with the smallest physical distance from the existing warehouse position of the same material;

[0081] The warehouse-out allocation module 30 is used for executing an expiration priority rule and a scattered priority rule and allocating spatially adjacent warehouse positions for the same order in response to a warehouse-out request; wherein the expiration priority rule is to select a warehouse position of the earliest expired batch; and the scattered priority rule is to preferentially select a partially occupied warehouse position under the condition of meeting the expiration rule.

[0082] The warehouse position marking module 40 is used for marking a warehouse position as a “to-be-continued” state if the warehouse position is not emptied after being taken off the shelf, and preferentially allocating the “to-be-continued” warehouse position for a subsequent task until the warehouse position is completely emptied.

[0083] The warehouse position updating module 50 is used for updating a warehouse position state database after each operation, for sharing and calling during shelving, warehousing and warehousing-out.

[0084] Embodiment three

[0085] The present application provides a terminal, the terminal includes a memory, a processor and a computer program stored in the memory, the computer program is executed by the processor to realize each step of the automatic warehouse position allocation method based on the warehouse management system as described in any one of the above embodiments.

[0086] Embodiment four

[0087] The present application provides a computer readable storage medium, the computer readable storage medium stores a computer program, the computer program is executed by the processor to realize each step of the automatic warehouse position allocation method based on the warehouse management system as described in any one of the above embodiments.

[0088] Embodiment five

[0089] The fifth aspect of the present application provides a computer program product, including a computer program or instructions, the computer program or instructions are executed by the processor to realize each step of the automatic warehouse position allocation method based on the warehouse management system as described in any one of the above embodiments.

[0090] In summary, the automatic warehouse position allocation method, device, terminal and computer storage medium based on the warehouse management system provided by the present application have the following beneficial effects:

[0091] (1) Efficiency improvement: through adjacent allocation and state optimization, the shelving / descaling time is reduced by 25%-40%, especially suitable for high-frequency warehouses (such as logistics centers handling thousands of orders per day);

[0092] (2) Cost savings: reduce personnel movement and equipment wear and tear (such as shortened forklift path), and reduce operating costs by 15%-20%;

[0093] (3) Error rate reduction: Automated state tracking avoids human errors (such as misplacing storage locations), improving inventory accuracy to over 99%;

[0094] (4) Commercial value: Enhancing the competitiveness of WMS systems, suitable for global supply chains (such as cross-border e-commerce), with potential market value of tens of billions of yuan;

[0095] (5) Innovation: Combining spatial algorithms, priority rules, and real-time feedback, it is the first of its kind in the industry.

[0096] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the system is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific name of each functional unit and module is only for easy distinction, and does not limit the protection scope of the application. The specific working process of the unit and module in the above system can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0097] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in a certain embodiment can be referred to the relevant description of other embodiments.

[0098] Those of ordinary skill in the art can realize that the units and method steps of the examples described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0099] In the embodiments of the present application, it should be understood that the disclosed system or device / terminal equipment and method can be implemented in other manners. For example, the system or device / terminal equipment embodiments described above are merely illustrative. For example, the division of the modules or units is merely logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, and there can be electric, mechanical or other forms.

[0100] The units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0101] In addition, each functional unit in the various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated in one unit. The integrated unit can be implemented in the form of hardware, or in the form of a software functional unit.

[0102] The present application is not limited to the description and the embodiments described in the specification, and those skilled in the art can easily implement other advantages and modifications, and therefore the present application is not limited to the specific details, representative devices and the illustrated examples shown and described herein.

Claims

1. A method for automatically allocating a storage location based on a warehouse management system, characterized in that, Comprise: Establish the hierarchical mapping relationship of warehouse, location, and storage location, configure the storable storage location set based on material attributes, and update the storage location occupation state in real time; After receiving the warehouse-in task, match the assignable storage location set according to the material type, and preferentially select the continuous empty storage location with the smallest physical distance from the existing same-material storage location; When responding to the warehouse-out request, execute the expiration priority rule and the scattered priority rule, and allocate spatially adjacent storage locations for the same order; wherein the expiration priority rule is to select the storage location of the earliest expiration batch; the scattered priority rule is to preferentially select the partially occupied storage location under the condition of meeting the expiration; After unloading, if the storage location is not empty, mark it as "to be continued" state, and the subsequent task is preferentially allocated to the "to be continued" storage location until it is completely emptied; Update the storage location state database after each operation for shared calling when shelving, warehousing, and unloading.

2. The method for automatically assigning a storage location based on a warehouse management system of claim 1, wherein, Establish the hierarchical mapping relationship of warehouse, location, and storage location, configure the storable storage location set based on material attributes, and update the storage location occupation state in real time, specifically comprising: Calculate the heat value of each material according to the historical warehouse-out frequency prediction formula, which is as follows: H = λ * log N d + (1 - λ) * N a , λ ∈ (0, 1) In the formula, H is the thermal value of the material, N d is the average number of times of taking out the material per day, N a is the average storage days of the material, and λ is the configuration weight. Map the high-frequency materials with the top H value to the location closest to the exit.

3. The method for automatically assigning a storage location based on a warehouse management system of claim 1, wherein, The implementation of the minimum physical distance specifically comprises: Construct a storage location network topology graph with channel intersection points as nodes; Use Dijkstra algorithm to calculate the shortest path from the current operation point to the target storage location; the calculation method is: min(∑e i *w i ), i is an edge between adjacent nodes, e i is the weight of edge i, w i = 1 + η * channel congestion index; η is a configuration weight with a value interval of (0, 1).

4. The method for automatically assigning a storage location based on a warehouse management system of claim 1, wherein, The execution of the expiration priority rule and the scattered priority rule is realized through multi-objective decision, specifically comprising: Calculate the comprehensive priority score P of the storage location based on the following formula: T c is the current date, T min is the earliest expiration date, T max is the latest expiration date, R is the occupancy rate of the storage location in the to-be-placed zone, and α and β are preset configuration weights. Select the storage location with the highest P value for allocation.

5. The method for automatically assigning storage locations based on a warehouse management system of claim 1, wherein, After unloading, if the storage location is not empty, mark it as "to be continued" state, and the subsequent task is preferentially allocated to the "to be continued" storage location until it is completely emptied In the step, it also includes:

6. The method for automatically assigning storage locations based on a warehouse management system of claim 1, wherein, When the proportion of "to be continued" state storage locations in a location is greater than a preset proportion threshold, automatically execute: retrieve all partially occupied storage locations in the location, and generate a storage location merging task and allocate it to an idle device. It also includes the step:

7. A device for automatically assigning a storage location based on a warehouse management system, characterized in that, Real-time display the storage location state heat map through different colors, and trigger sound and / or light alarm when the storage location is overdue. Comprise: A storage location configuration module for establishing the hierarchical mapping relationship of warehouse, location, and storage location, configuring the storable storage location set based on material attributes, and updating the storage location occupation state in real time; A warehouse-in allocation module for matching the assignable storage location set according to the material type after receiving the warehouse-in task, and preferentially selecting the continuous empty storage location with the smallest physical distance from the existing same-material storage location; A warehouse-out allocation module for executing the expiration priority rule and the scattered priority rule when responding to the warehouse-out request, and allocating spatially adjacent storage locations for the same order; wherein the expiration priority rule is to select the storage location of the earliest expiration batch; the scattered priority rule is to preferentially select the partially occupied storage location under the condition of meeting the expiration; A storage location marking module for marking the storage location as "to be continued" state if it is not empty after unloading, and preferentially allocating the "to be continued" storage location to the subsequent task until it is completely emptied; A storage location updating module for updating the storage location state database after each operation for shared calling when shelving, warehousing, and unloading.

8. A terminal, characterized by comprising: The terminal comprises a memory, a processor, and a computer program stored in the memory, and the computer program, when executed by the processor, implements each step of the warehouse management system-based automatic allocation of storage locations method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program, when executed by a processor, implements each step of the warehouse management system-based automatic allocation of storage locations method according to any one of claims 1-6.

Images