Warehouse storage location allocation method and device based on storage location score and material popularity

Abstract

The invention discloses a warehousing storage location allocation method and device based on storage location scores and material popularity, and belongs to the technical field of warehouse management. The warehousing storage location allocation method comprises the following steps: obtaining warehousing order information; calculating a storage position score of each available storage position according to the actual carrying distance, and calculating a material score of each material; dividing all the materials into a plurality of sets according to the material priorities, wherein the materials in the same set have the same priority; for each material in the same priority set, calculating an average absolute error between the material score of the material and the scores of all available storage locations under the corresponding order, and sorting the materials according to the average absolute error; and sequentially processing each priority set according to a sequence of priorities from high to low, and for the materials in the same priority set, distributing the materials to the currently available storage positions with the highest storage position scores one by one according to a sequence of average absolute errors from small to large. The overall carrying cost in the ex-warehouse process can be effectively reduced, and the warehousing operation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of warehouse management technology, and in particular to a method and apparatus for allocating storage locations upon entry into the warehouse based on storage location scoring and material heat. Background Technology

[0002] In a warehousing system, material inbound storage location allocation refers to the process by which the system assigns one or more optimal storage locations to materials after they arrive at the warehouse. This allocation process directly affects the warehouse's space utilization efficiency and the overall effectiveness of outbound operations. A reasonable storage location strategy needs to comprehensively consider the outbound characteristics of materials upon inbound, such as outbound frequency and turnover characteristics. Materials with higher outbound frequency should be prioritized for allocation to storage locations closer to warehouse entrances or workstations with shorter picking paths, thereby shortening the overall picking distance and reducing handling costs.

[0003] Currently, common storage location allocation methods mostly adopt the ABC classification strategy, which divides materials into three categories: A (particularly important), B (generally important), and C (not important) based on indicators such as total quantity, value, and shelf life. A-class materials are then placed in areas closer to the exit or workstation, while C-class materials are placed in relatively remote locations to optimize handling efficiency.

[0004] While this method can meet the basic needs of warehouse management to some extent, it still has significant limitations. First, ABC classification typically relies on manual experience to assign material categories, making it difficult to efficiently and consistently handle multi-category, large-scale, and dynamically changing warehouse material environments, resulting in insufficient automation and adaptability. More importantly, this strategy only achieves coarse-grained classification at the broad category level, failing to further differentiate the outbound dynamics of different materials within the same category. This leads to some A-category materials with low outbound frequency occupying prime storage locations for extended periods, while B or C-category materials with frequent outbound movements fail to receive corresponding priority allocation, resulting in underutilization of core storage resources and hindering further improvements in overall inbound and outbound efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for allocating storage locations based on storage location scoring and material heat, in order to solve the problems of low efficiency and poor adaptability caused by the reliance on manual static designation of material categories in existing storage location allocation methods, as well as the waste of high-quality storage location resources and reduced overall warehousing efficiency caused by the failure to consider the differences in the outbound frequency of similar materials.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] This application discloses a method for allocating storage locations upon entry into the warehouse based on storage location scoring and material heat, comprising the following steps:

[0008] 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.

[0009] 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's historical popularity.

[0010] All materials are divided into multiple sets according to material priority, and materials in the same set have the same priority.

[0011] 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;

[0012] The priority sets are processed sequentially from highest to lowest 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 order of increasing average absolute error.

[0013] Preferably, the actual transport distance includes: the minimum and maximum transport distances from each available storage location within the order to the corresponding workstation, and the transport distance from the current storage location to be rated to the corresponding workstation.

[0014] Preferably, the calculation of the storage location score for each available storage location based on the actual transport distance includes:

[0015] 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;

[0016] Calculate the difference between the maximum and minimum transport distances, and use it as the second difference.

[0017] Divide the first difference by the second difference and then multiply by the first preset multiple to obtain the storage space score;

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

[0019] Preferably, the calculation of the material score for each material based on the material priority and historical popularity includes:

[0020] The current material heat is estimated based on the material's historical heat, and a heat score is obtained after normalization.

[0021] 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;

[0022] 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.

[0023] Preferably, the mean absolute error represents the average of the absolute differences between the scores of the same material and its various available storage locations.

[0024] Preferably, the step of allocating each storage location to the currently available storage location with the highest storage location score includes:

[0025] 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;

[0026] 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.

[0027] 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.

[0028] As a preferred option, after allocation is completed, output the remaining quantity of materials in each order that were not successfully allocated.

[0029] A storage location allocation device based on storage location scoring and material temperature includes:

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] An electronic device includes a memory and a processor, the memory being 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 the preceding descriptions.

[0036] A computer-readable storage medium storing a computer program that, when executed by a computer, implements a method for allocating storage locations based on storage location scoring and material heat as described in any one of the preceding descriptions.

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

[0038] This application, based on user-specified material priorities, comprehensively evaluates the importance of materials by combining dynamic material popularity data. It also 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. This effectively reduces overall handling costs during the outbound process and improves warehousing efficiency. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart of a method for allocating storage locations based on storage location scoring and material heat, provided in an embodiment of this application.

[0041] Figure 2 This is a schematic diagram of the iterative allocation process provided in the embodiments of this application;

[0042] Figure 3 This is a schematic diagram of the structure of an inbound storage location allocation device based on storage location scoring and material heat provided in an embodiment of this application;

[0043] Figure 4 This is a schematic diagram of an electronic device that implements a method for allocating storage locations based on storage location scoring and material heat, as provided in an embodiment of this application. Detailed Implementation

[0044] To make the technical solution of this application clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The terms "first," "second," etc., in the claims and specification of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate. This is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of units is not necessarily limited to those units, but may include other units not explicitly listed or inherent to these processes, methods, products, or apparatuses.

[0045] Example 1

[0046] like Figure 1 As shown, a method for allocating storage locations upon entry into a warehouse based on storage location scoring and material heat includes the following steps:

[0047] S110. Obtain inbound order information. Inbound order information 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.

[0048] S120. Calculate the storage location score for each available storage location based on the actual handling distance, and calculate the material score for each material based on material priority and material historical popularity.

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

[0050] S140. 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.

[0051] S150. Process each priority set in descending order of priority. For materials within the same priority set, allocate them one by one to the currently available storage location with the highest storage location score in ascending order of average absolute error.

[0052] In this embodiment, the first step is to obtain the inbound order information, which can be represented as an inbound order list. This list contains detailed information on all currently pending orders. Each order information includes at least the material priority, the material's historical popularity, the available storage locations, and the actual handling distance from each available storage location to its corresponding workstation.

[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 and the remaining amount of unallocated material M3 are 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's historical popularity. 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 sequentially from highest to lowest 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 order of increasing average absolute error.

2. The method for allocating storage locations based on storage location scoring and material heat according to claim 1, characterized in that, The actual handling distance includes: the minimum and maximum handling distances from each available storage location within the order to the corresponding workstation, and the handling distance from the current storage location to be scored to the corresponding workstation.

3. The method for allocating storage locations based on storage location scoring and material heat according to claim 2, characterized in that, 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.

4. The method for allocating storage locations based on storage location scoring and material heat according to claim 1, characterized in that, 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.

5. 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.

6. 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.

7. The method for allocating storage locations based on storage location scoring and material heat according to claim 6, characterized in that, After allocation is completed, output the remaining quantity of materials in each order that were not successfully allocated.

8. 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 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.

9. An electronic device, characterized in that, The system 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 7.

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

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