Storage location assignment method and device based on storage location score and material heat

Abstract

The application discloses a kind of based on storage location score and material heat's warehouse storage location distribution method and device, belong to warehouse management technical field, comprising: obtaining warehouse order information;According to actual carrying distance, the storage location score of each available storage location is calculated, and the material score of each material is calculated;According to material priority, all materials are divided into multiple sets, and the materials in the same set have the same priority;For each material in the same priority set, the average absolute error between its material score and the score of all available storage locations under the corresponding order is calculated, and the material is sorted according to the average absolute error;In order of priority from high to low, each priority set is processed in turn, and for the materials in the same priority set, in order of average absolute error from small to large, they are allocated to the current available and highest storage location score storage location one by one.The application can effectively reduce the overall carrying cost in the process of delivery, improve the efficiency of warehouse operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of warehouse management, and in particular to a warehouse storage space allocation method and device based on storage space scoring and material heat. BACKGROUND

[0002] In a warehouse operation system, warehouse storage space allocation of materials refers to the process of assigning one or more optimal storage spaces to the materials for storage after the materials arrive at the warehouse. This allocation process directly affects the space utilization efficiency of the warehouse and the overall performance of the warehouse operation. A reasonable storage space strategy needs to consider the warehouse-out characteristics of the materials, such as warehouse-out frequency, turnover characteristics, etc., when the materials are warehoused, and preferentially allocate materials with high warehouse-out frequency to storage spaces close to the warehouse entrance or operation station or with shorter picking paths, so as to shorten the overall picking distance and reduce the transportation cost.

[0003] Currently, common storage space allocation methods mostly use the ABC classification strategy, that is, according to the total amount, value, shelf life, etc. of the materials, they are divided into A (very important), B (generally important) and C (unimportant) three categories, and accordingly, the A class materials are arranged in the area close to the exit or station, and the C class materials are arranged in the relatively remote position, so as to optimize the transportation efficiency.

[0004] Although this method can meet the basic needs of warehouse management to some extent, it still has obvious limitations. First, ABC classification usually relies on manual experience to assign material categories, and it is difficult to efficiently and consistently cope with a multi-category, large-scale and dynamically changing warehouse material environment, and it lacks automation and adaptability. More importantly, this strategy only realizes coarse-grained division at the large category level, and does not further distinguish the warehouse-out dynamics of different materials within the same category, resulting in that some A class materials with low warehouse-out frequency occupy high-quality storage spaces for a long time, while B class or C class materials with high warehouse-out frequency cannot obtain corresponding preferential allocation, causing insufficient utilization of core storage space resources and restricting the further improvement of overall warehouse-in and warehouse-out efficiency. SUMMARY

[0005] The present application aims to provide a warehouse storage space allocation method and device based on storage space scoring and material heat, to solve the problems of low efficiency and poor adaptability caused by relying on manual static assignment of material categories in the prior art, and the waste of high-quality storage space resources and the reduction of overall warehouse-in and warehouse-out efficiency caused by not considering the differences in warehouse-out frequency of materials of the same category.

[0006] To achieve the above-mentioned purpose, the following technical solutions are adopted in the present application:

[0007] The warehouse storage space allocation method based on storage space scoring and material heat of the present application comprises the following steps:

[0008] Obtaining warehouse-in order information, the warehouse-in order information including material priority of each order, material historical heat, available storage locations, and actual carrying distance of each available storage location to corresponding workstations;

[0009] Calculating storage location scores of each available storage location according to the actual carrying distance, and calculating material scores of each material based on the material priority and the material historical heat;

[0010] Dividing all materials into multiple sets according to the material priority, materials in the same set having the same priority;

[0011] For each material in the same priority set, calculating the average absolute error between the material score and the scores of all available storage locations under the corresponding order, and sorting the materials according to the average absolute error;

[0012] Processing each priority set in turn in the order of priority from high to low, and assigning each material in the same priority set to the current available storage location with the highest storage location score in the order of average absolute error from small to large.

[0013] As a preferred, the actual carrying distance includes: the minimum carrying distance and the maximum carrying distance of each available storage location to the corresponding workstation, and the carrying distance of the current storage location to be scored to the corresponding workstation.

[0014] As a preferred, the calculating the storage location scores of each available storage location according to the actual carrying distance includes:

[0015] Calculating the difference between the maximum carrying distance and the carrying distance of the current storage location to be scored to the corresponding workstation as a first difference;

[0016] Calculating the difference between the maximum carrying distance and the minimum carrying distance as a second difference;

[0017] Dividing the first difference by the second difference and multiplying by a first preset multiple to obtain the storage location score;

[0018] Wherein, if the maximum carrying distance is equal to the minimum carrying distance, the storage location score takes a preset fixed value.

[0019] As a preferred, the calculating the material scores of each material based on the material priority and the material historical heat includes:

[0020] Estimating the current material heat based on the material historical heat, and obtaining a heat score after normalization processing;

[0021] If the material priority is specified by a user, adding the heat score to the user-specified material priority to obtain the material score;

[0022] If the user does not specify the material priority, a default priority value is used, and the hotness score is multiplied by a second preset multiple to obtain a material score.

[0023] Preferably, the average absolute error represents the average of the absolute differences between the same material and each available storage location score.

[0024] Preferably, the one-by-one allocation to the currently available and highest storage location score storage location includes:

[0025] According to the remaining amount of the material of the current order to be allocated and the remaining capacity of the target storage location, the current allocation amount is determined;

[0026] According to the current allocation amount, a matching relationship between the material and the storage location is established, and the remaining amount of the material of the current order to be allocated and the remaining capacity of the target storage location are updated accordingly;

[0027] The above process is iterated until any one of the following conditions is met: all material allocation is completed, all storage locations are full, or all priority sets are processed.

[0028] Preferably, after the allocation is completed, the remaining amount of the material in each order that is not successfully allocated is output.

[0029] A storage location allocation device based on storage location score and material hotness includes:

[0030] An acquisition module is configured to acquire warehouse-in order information, the warehouse-in order information including material priority, material historical hotness, available storage locations, and actual carrying distances from each available storage location to a corresponding work location of each order;

[0031] A calculation module is configured to calculate a storage location score of each available storage location according to the actual carrying distances, and calculate a material score of each material based on the material priority and the material historical hotness;

[0032] A division module is configured to divide all materials into multiple sets according to the material priority, and materials in the same set have the same priority;

[0033] An ordering module is configured to calculate, for each material in the same priority set, an average absolute error between the material score and all available storage location scores of the corresponding order, and order the materials according to the average absolute error;

[0034] An allocation module is configured to process each priority set in order from high to low priority, and for materials in the same priority set, allocate one by one to the currently available and highest storage location score storage location in order from small to large average absolute error.

[0035] An electronic device comprises a memory and a processor, the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the storage location scoring and material heat-based storage location allocation method in any one of the above.

[0036] A computer readable storage medium storing a computer program, the computer program enables a computer to execute the storage location scoring and material heat-based storage location allocation method in any one of the above when executed.

[0037] The present application has the following beneficial effects:

[0038] The present application can evaluate the importance of materials in combination with dynamic material heat data on the premise of user-specified material priority, and objectively measure the value of storage locations according to the distance from available storage locations to workstations, and finally realize the optimization of allocating storage locations through the importance matching strategy. That is, the present application provides storage locations closer to workstations for materials with high priority and high frequency of outbound, and allocates materials with low priority and low frequency of outbound to relatively remote storage locations, which can effectively reduce the overall handling cost in the outbound process and improve the efficiency of warehouse operation. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0040] Figure 1 is a flowchart of a storage location scoring and material heat-based storage location allocation method provided by an embodiment of the present application;

[0041] Figure 2 is an iterative allocation process schematic diagram provided by an embodiment of the present application;

[0042] Figure 3 is a structural schematic diagram of a storage location scoring and material heat-based storage location allocation device provided by an embodiment of the present application;

[0043] Figure 4 is an electronic device schematic diagram for implementing a storage location scoring and material heat-based storage location allocation method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0044] For the technical solutions of the present application to be more clear, the present application is further described in detail below in combination with the drawings and specific embodiments. The terms "first", "second", etc. in the claims and the description of the present application are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, which is only a way of distinguishing the objects with the same attributes in the description of the embodiments of the present application. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, so that the processes, methods, systems, products or equipment containing a series of units do not have to be limited to those units, but can include other units not clearly listed or inherent to these processes, methods, products or equipment.

[0045] Embodiment 1

[0046] As Figure 1 shown, a storage space allocation method based on storage space score and material heat includes the following steps:

[0047] S110, obtaining warehouse-in order information, the warehouse-in order information including material priority, material historical heat, available storage space and actual carrying distance of each available storage space to the corresponding work station of each order;

[0048] S120, calculating the storage space score of each available storage space according to the actual carrying distance, and calculating the material score of each material based on the material priority and the material historical heat;

[0049] S130, dividing all materials into multiple sets according to the material priority, and the materials in the same set have the same priority;

[0050] S140, for each material in the same priority set, calculating the average absolute error between the material score and the score of all available storage spaces of the corresponding order, and sorting the materials according to the average absolute error;

[0051] S150, processing each priority set in order of priority from high to low, and for the materials in the same priority set, assigning them one by one to the current available storage space with the highest storage space score in order of average absolute error from small to large.

[0052] In this embodiment, the warehouse-in order information is first obtained, which can be specifically manifested as a warehouse-in order list containing detailed information of all current orders to be processed. Each order information at least includes material priority, material historical heat, available storage space and actual carrying distance of each available storage space to its corresponding work station.

[0053] Material priority can be manually set by the user according to business needs, which reflects the urgency or importance of the material in the current operation; material historical popularity is calculated based on the frequency of the material's outbound movement over a period of time, which is used to measure its inbound and outbound activity. The higher the popularity, the more often the material is called, and it should usually be prioritized for allocation to high-quality storage locations that are close to the warehouse entrance or workstation and have shorter picking paths.

[0054] Furthermore, to achieve intelligent and efficient allocation of storage locations, it is necessary to comprehensively score each available storage location under each order, that is, to calculate the storage location score B. score This quantifies the optimality of the storage location in the current context. The score is primarily based on the actual transport distance between each available storage location and its corresponding workstation under an order, and is normalized by incorporating the global distance distribution. It should be noted that the actual transport distance from each available storage location to its corresponding workstation under an order includes not only the minimum transport distance D from each available storage location to its corresponding workstation under that order. min and maximum transport distance D max It also includes the actual transport distance D from the current storage location to the corresponding workstation. The evaluation specifically includes the following steps:

[0055] Calculate the maximum transport distance D max The difference between the current storage location to be evaluated and the transport distance D from the corresponding workstation is taken as the first difference D. max -D;

[0056] Calculate the maximum transport distance D max With minimum transport distance D min The difference D max -D min , as the second difference;

[0057] Then, the storage score B is calculated using a linear normalization method. score The calculation involves dividing the first difference by the second difference and then multiplying by a first preset multiple. The specific calculation formula is as follows:

[0058] ,

[0059] Wherein, 2 is the first preset multiple, which can be adjusted according to actual needs, and is usually taken as a positive value.

[0060] When D max =D min When all available storage locations are equidistant from the corresponding workstation of an order, the storage location score is B. score Take a fixed value of 1; when D=D min That is, when the distance from the current storage location to the corresponding workstation of the order is the minimum handling distance, the storage location is rated B. score The preset fixed value is 2, which can also be adjusted according to actual needs; when D=Dmax That is, when the transport distance from the current storage location to the corresponding workstation of the order is the maximum transport distance, the storage location is rated B. score Take the minimum value of 0.

[0061] This embodiment constructs a dynamic and adaptive storage location scoring mechanism by quantitatively analyzing the actual handling distance. This scoring mechanism allows available storage locations with shorter actual handling distances to receive higher scores, which helps improve warehousing operation efficiency and reduce overall handling costs. Furthermore, through normalization processing, the scoring results have good comparability and consistency under different layout environments.

[0062] Based on the acquired inbound order information, a dynamic and configurable material scoring mechanism is constructed using historical material popularity and material priority to quantify the overall importance of each material in the current warehouse scheduling environment. This score will serve as an important basis for subsequent decision-making processes such as allocating storage space and sequencing operations.

[0063] Furthermore, material rating M score The calculation process is as follows:

[0064] The current material popularity is estimated based on the material's historical popularity, and a popularity score is obtained after normalization.

[0065] If the material priority is specified by the user, the popularity score is added to the material priority specified by the user to obtain the material score;

[0066] If the user does not specify a material priority, the default priority value will be used, and the popularity score will be multiplied by the second preset multiplier to obtain the material score.

[0067] Specifically, based on the historical popularity of materials recorded in the order, a time series analysis method is first used to determine the current popularity H of the materials. p To predict the future availability and frequency of the material, a prediction model can be used, either a linear fitting model or an ARIMA model. Linear fitting models are suitable for materials with stable and gradual heat trends, while ARIMA models are suitable for historical data with periodic or trend-like fluctuations, and can more accurately capture heat change trends. Simultaneously, to eliminate differences in heat units and orders of magnitude between different materials, the predicted heat value H is... p Normalization is performed to convert it into a standardized popularity score M. h Normalization methods can include Min-Max normalization, Z-score standardization, or quantile-based mapping to ensure that scores fall within a reasonable range (e.g., [0,1]), thereby improving the comparability of material scores and the adaptability of the system.

[0068] Next, determine the material priority M in the current order. pIs it an empty value? If the material priority in the order is M p If the value is not empty, it means that the user has specified a material priority, that is, the material has clear business importance (such as urgent orders, high-value materials, etc.). In this case, the manually set material priority M will be applied. p With popularity rating M h The sum is the material score M. score M score =M p +M h This method retains the flexibility of human intervention while taking into account the natural activity of materials, achieving a dual-drive of "rules + data".

[0069] If the material priority in the order is M p If the value is empty, it means the user has not specified a material priority. In this case, the default priority will be used, and the material heat value M will be directly assigned. h Multiplying by a second preset factor, in this embodiment, the default priority value is 0.5, and the second preset factor is 2, M score =2*M h This method avoids scoring gaps caused by a lack of human input, while ensuring that heat-driven materials still receive reasonable scheduling weights through multiplier adjustments.

[0070] This embodiment constructs a material scoring mechanism that combines automation and flexibility by integrating data-driven heat prediction with a configurable prioritization strategy. This mechanism can not only dynamically respond to changes in material usage patterns but also accommodate the need for manual intervention, effectively supporting efficient and accurate decision-making in intelligent warehousing systems under complex and ever-changing environments.

[0071] After obtaining the storage location score and material score, the storage location allocation operation can be performed. Specifically, during the allocation process, all orders are first divided into several sets according to material priority, with materials in the same set having the same material priority. Then, for materials in the same priority set, the average of the absolute differences between the material score of each material and the storage location scores of all available storage locations under the corresponding order is calculated, i.e., the Mean Absolute Error (MAE). score and according to MAE score The value sorts the materials within this priority set in ascending order. In this embodiment, MAE score The smaller the value, the higher the degree of matching between the material and the storage location.

[0072] Among them, MAE score The calculation formula is as follows:

[0073] ,

[0074] N represents the number of available storage locations corresponding to this material, i.e., the number of available storage locations under this order; Bi score This represents the storage score of the i-th available storage location.

[0075] Next, each priority set is processed sequentially in descending order of priority, and materials within the same priority set are processed according to MAE. score Storage locations are allocated sequentially from smallest to largest. For example... Figure 2 As shown, the allocation process includes the following iterative steps:

[0076] S210. Determine the current allocation quantity based on the remaining quantity of materials in the current order to be allocated and the remaining capacity of the target storage location;

[0077] S220. Based on the current allocation quantity, establish a matching relationship between materials and storage locations, and update the remaining quantity of materials and the remaining capacity of the target storage location for the current order to be allocated accordingly.

[0078] S230. Iterate the above process until any one of the following conditions is met: all materials have been allocated, all storage locations are full, or all priority sets have been processed.

[0079] More specifically, in each round of matching, the remaining material quantity of the current order and the remaining capacity of its available storage locations are compared first. The smaller value is taken as the actual amount of material that can be stored, i.e., the current allocation quantity. The matching relationship between materials and storage locations is recorded accordingly, and the result is output. At the same time, the remaining material quantity of the current order and the remaining capacity of the corresponding storage location are also reduced by the actual amount of material that can be stored. If all materials for all orders have been allocated, or all storage locations are full, or all sets have been processed, the allocation process terminates, and the remaining unallocated material quantity in all orders is finally counted and output; otherwise, the priority set is accessed and storage location matching continues.

[0080] Assuming the current material priority is M p The priority sets, arranged from highest to lowest, are: set A (M) p =0.9) → Set B (M p =0.7) → Set C (M p =0.5), where, within set A, according to MAE score The materials arranged from smallest to largest are M1 (MAE) score =0.54) → M2 (MAE score =0.84); there exists only one MAE in set B. score Material M3 has a value of 0.9; set C contains only one MAE. score Material M4 has a value of 0.95. All four materials have available storage locations, including storage location S1 (B). score =2), S2(B score =1.5) and S3 (Bscore =1).

[0081] The initial resource status is as follows:

[0082] Material remaining quantity: M1=2, M2=1, M3=1, M4=1 (assuming M1 has 2 units of inventory).

[0083] Remaining storage capacity: S1=1, S2=2, S3=1 (assuming that available storage space S2 can hold 2 units).

[0084] Then, iterative allocation is performed according to the order of set A → set B → set C, and within each set, in the order of M1 → M2 → M3 → M4. Specifically, in the first round, material M1 is processed, and the current optimal available storage location is S1 (B score =2), here S1 is taken as the best available storage location because it has the highest storage location score, that is, its transportation distance from the corresponding workstation is the smallest. First, determine the allocation quantity min(material M1 remaining quantity 2, storage location S1 remaining capacity 1) =1, then establish the matching relationship, that is, store 1 unit of M1 into S1 and update the remaining information, that is, the material M1 remaining quantity is 2-1=1, and the storage location S1 remaining capacity is 1-1=0 (S1 is full).

[0085] The current resource status is as follows:

[0086] Material remaining quantity: M1=1, M2=1, M3=1, M4=1.

[0087] Remaining storage capacity: S1=0, S2=2, S3=1.

[0088] In the second iteration, material M1 is processed again, and the current optimal available storage location is S2 (B). score =1.5), first determine the allocation quantity min(Material M1 remaining quantity 1, storage location S2 remaining capacity 2) =1, then establish the matching relationship, that is, store 1 unit of M1 into S2, and update the remaining information. The remaining quantity of material M1 is 1-1=0 (M1 has been allocated), and the remaining capacity of storage location S2 is 2-1=1.

[0089] The current resource status is as follows:

[0090] Material remaining quantity: M1=0, M2=1, M3=1, M4=1.

[0091] Remaining storage capacity: S1=0, S2=1, S3=1.

[0092] In the third iteration, material M2 is processed, and the current optimal available storage location is S2 (B). score=1.5), first determine the allocation amount min (material M1 remaining amount 1, storage location S2 remaining capacity 1) =1, then establish the matching relationship, that is, store 1 unit of M2 into S2, and update the remaining information. The remaining amount of material M2 is 1-1=0 (M2 has been allocated), and the remaining capacity of storage location S2 is 1-1=0 (S2 is full).

[0093] The current resource status is as follows:

[0094] Material remaining quantity: M1=0, M2=0, M3=1, M4=1.

[0095] Remaining storage capacity: S1=0, S2=0, S3=1.

[0096] In the fourth iteration, material M3 is processed, and the current optimal available storage location is S3 (B). score =1), first determine the allocation amount min (material M3 remaining amount 1, storage location S3 remaining capacity 1) =1, then establish the matching relationship, that is, store 1 unit of M3 into S3 and update the remaining information. The remaining amount of material M3 is 1-1=0 (M3 has been allocated), and the remaining capacity of storage location S3 is 1-1=0 (S3 is full).

[0097] The current resource status is as follows:

[0098] Material remaining quantity: M1=0, M2=0, M3=0, M4=1.

[0099] Remaining storage capacity: S1=0, S2=0, S3=0.

[0100] At this point, all available storage locations are full, the allocation process ends automatically, and the final allocation result, as well as the remaining amount of unallocated material M3, is output.

[0101] The storage location allocation method provided in this embodiment can comprehensively evaluate the importance of materials by combining dynamic material popularity data with the user-specified material priority. Simultaneously, it objectively measures the value of storage locations based on the distance from available storage locations to workstations, and finally optimizes storage location allocation through an importance matching strategy. In other words, this solution prioritizes providing storage locations closer to workstations for high-priority, frequently dispatched materials, while allocating low-priority, infrequently dispatched materials to relatively remote storage locations, effectively reducing overall handling costs during the dispatch process and improving warehousing efficiency.

[0102] Example 2

[0103] like Figure 3 As shown, a storage location allocation device based on storage location scoring and material temperature includes:

[0104] The acquisition module is used to acquire inbound order information, which includes the material priority, historical popularity of materials, available storage locations, and the actual handling distance from each available storage location to the corresponding workstation for each order.

[0105] The calculation module is used to calculate the storage location score of each available storage location based on the actual handling distance, and to calculate the material score of each material based on material priority and material historical popularity.

[0106] The partitioning module is used to divide all materials into multiple sets based on material priority, with materials in the same set having the same priority.

[0107] The sorting module is used to calculate the average absolute error between the material score and the scores of all available storage locations under the corresponding order for each material within the same priority set, and sort the materials according to the average absolute error.

[0108] The allocation module is used to process each priority set in descending order of priority. For materials within the same priority set, they are allocated one by one to the currently available storage location with the highest storage location score, in ascending order of average absolute error.

[0109] This embodiment is used to implement the method provided in the above embodiments and has the corresponding beneficial effects of the method. Technical details not described in detail in this embodiment can be found in the methods provided in all the foregoing embodiments of this invention.

[0110] Example 3

[0111] like Figure 4 As shown, an electronic device includes a memory 401 and a processor 402. The memory 401 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 402 to implement the above-described method for allocating storage locations based on storage location scoring and material heat.

[0112] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the electronic device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0113] A computer-readable storage medium storing a computer program that, when executed by a computer, implements the above-described method for allocating storage locations based on storage location scoring and material heat.

[0114] For example, a computer program can be divided into one or more modules / units. One or more modules / units are stored in memory 401 and executed by processor 402. Data I / O interface transmission is completed by input interface 405 and output interface 406 to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions. The instruction segments are used to describe the execution process of the computer program in the computer device.

[0115] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device may include, but is not limited to, a memory 401 and a processor 402. Those skilled in the art will understand that this embodiment is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components, or a combination of certain components, or different components. For example, the computer device may also include an input device 407, a network access device, a bus, etc.

[0116] The processor 402 can be a Central Processing Unit (CPU), or other general-purpose processors 402, digital signal processors 402 (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor 402 can be a microprocessor 402, or any conventional processor 402, etc.

[0117] The memory 401 can be an internal storage unit of a computer device, such as a hard disk or memory. The memory 401 can also be an external storage device of a computer device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 401 can include both internal and external storage units. The memory 401 is used to store computer programs and other programs and data required by the computer device. The memory 401 can also be used for temporary storage in the output device 408. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM) 403, random access memory (RAM) 404, discs, or optical discs.

[0118] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for allocating storage locations upon entry into a warehouse based on storage location scoring and material heat, characterized in that, Includes the following steps: Obtain inbound order information, which includes the material priority, historical popularity of materials, available storage locations, and the actual handling distance from each available storage location to the corresponding workstation for each order. The storage location score for each available storage location is calculated based on the actual handling distance, and the material score for each material is calculated based on the material priority and the material historical popularity. The actual handling distance includes: the minimum and maximum handling distances from each available storage location in the order to the corresponding workstation, and the handling distance from the current storage location to be scored to the corresponding workstation. All materials are divided into multiple sets according to material priority, and materials in the same set have the same priority. For each material within the same priority set, calculate the average absolute error between its material score and the scores of all available storage locations under the corresponding order, and sort the materials according to the average absolute error; The priority sets are processed in descending order of priority. For materials within the same priority set, they are allocated to the storage location with the highest available storage location score in ascending order of average absolute error. The calculation of the storage location score for each available storage location based on the actual transport distance includes: Calculate the difference between the maximum transport distance and the transport distance from the current storage location to be evaluated to the corresponding workstation, and use it as the first difference; Calculate the difference between the maximum and minimum transport distances, and use it as the second difference. Divide the first difference by the second difference and then multiply by the first preset multiple to obtain the storage space score; Wherein, if the maximum transport distance is equal to the minimum transport distance, the storage location score takes a preset fixed value; The calculation of the material score for each material based on the material priority and historical popularity includes: The current material heat is estimated based on the material's historical heat, and a heat score is obtained after normalization. If the material priority is specified by the user, the popularity score is added to the material priority specified by the user to obtain the material score; If the user does not specify the material priority, the default priority value is used, and the popularity score is multiplied by the second preset multiple to obtain the material score.

2. The method for allocating storage locations based on storage location scoring and material heat according to claim 1, characterized in that, The mean absolute error represents the average of the absolute differences between the scores of the same material and its available storage locations.

3. The method for allocating storage locations based on storage location scoring and material heat according to claim 1, characterized in that, The process of allocating each storage location to the currently available storage location with the highest storage location score includes: The current allocation quantity is determined based on the remaining material quantity of the current orders to be allocated and the remaining capacity of the target storage location; Based on the current allocation amount, establish a matching relationship between materials and storage locations, and update the remaining material quantity and remaining capacity of the target storage location for the current order to be allocated accordingly. Iterate through the above process until any one of the following conditions is met: all materials have been allocated, all storage locations are full, or all priority sets have been processed.

4. The method for allocating storage locations based on storage location scoring and material heat according to claim 3, characterized in that, After allocation is completed, output the remaining quantity of materials in each order that were not successfully allocated.

5. A storage location allocation device based on storage location scoring and material temperature, characterized in that, include: The acquisition module is used to acquire inbound order information, which includes the material priority, historical popularity of materials, available storage locations, and the actual handling distance from each available storage location to the corresponding workstation for each order. The calculation module is used to calculate the storage location score of each available storage location based on the actual handling distance, and to calculate the material score of each material based on the material priority and the material historical popularity. The actual handling distance includes: the minimum handling distance and the maximum handling distance from each available storage location in the order to the corresponding workstation, and the handling distance from the current storage location to be scored to the corresponding workstation. The partitioning module is used to divide all materials into multiple sets based on material priority, with materials in the same set having the same priority. The sorting module is used to calculate the average absolute error between the material score and the scores of all available storage locations under the corresponding order for each material in the same priority set, and sort the materials according to the average absolute error. The allocation module is used to process each priority set in descending order of priority. For materials within the same priority set, they are allocated one by one to the currently available storage location with the highest storage location score in ascending order of average absolute error. The calculation of the storage location score for each available storage location based on the actual transport distance includes: Calculate the difference between the maximum transport distance and the transport distance from the current storage location to be evaluated to the corresponding workstation, and use it as the first difference; Calculate the difference between the maximum and minimum transport distances, and use it as the second difference. Divide the first difference by the second difference and then multiply by the first preset multiple to obtain the storage space score; Wherein, if the maximum transport distance is equal to the minimum transport distance, the storage location score takes a preset fixed value; The calculation of the material score for each material based on the material priority and historical popularity includes: The current material heat is estimated based on the material's historical heat, and a heat score is obtained after normalization. If the material priority is specified by the user, the popularity score is added to the material priority specified by the user to obtain the material score; If the user does not specify the material priority, the default priority value is used, and the popularity score is multiplied by the second preset multiple to obtain the material score.

6. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement a method for allocating storage locations based on storage location scoring and material calorific value as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, The computer program enables the computer to implement, when executed, a storage location allocation method based on storage location scoring and material heat as described in any one of claims 1 to 4.

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