Logistics sorting slot distribution method, device, equipment, medium and program product

Abstract

The application provides a logistics sorting bin distribution method, device, equipment, medium and program product. The method of the application comprises: determining a target logistics direction needing to be distributed in a logistics sorting scene and a quantity of bins needing to be distributed corresponding to the target logistics direction; according to bin distribution constraint information corresponding to the target logistics direction, a target distribution strategy is adopted to determine target bins meeting the quantity in a candidate resource pool, the candidate resource pool comprises static bins and backup bins, the static bins are bins configured with an unchangeable sorting plan, and the target distribution strategy comprises at least one of multiple strategies, i.e., a bin merging strategy and a bin supplement strategy, the bin merging strategy is used for merging static bins, and the bin supplement strategy is used for selecting backup bins; and the target bins are distributed to the target logistics direction. The application can solve the problem of low distribution efficiency existing in the existing bin distribution scheme.

Description

Technical Field

[0001] This application relates to the field of logistics, and in particular to a logistics sorting compartment allocation method, apparatus, equipment, medium, and procedure product. Background Technology

[0002] In automated logistics sorting scenarios, the number of sorting slots is usually fixed, and the load on different logistics directions fluctuates significantly across different dates, locations, and shifts. When the load on a particular logistics direction increases sharply, it is often necessary to allocate additional slots to meet the sorting demand. However, since the total number of slots in a logistics sorting scenario is limited, additional slots can only be obtained from existing slots. Existing slot allocation schemes typically rely on manual analysis of existing sorting plans and the load status of each slot to identify available slots and reallocate them. However, this allocation process requires manual checking of multiple slots one by one and judgment based on various allocation constraints, resulting in extremely low allocation efficiency. Summary of the Invention

[0003] This application provides a method, apparatus, equipment, medium, and program product for logistics sorting and allocation, in order to solve the problem of low allocation efficiency in existing sorting and allocation schemes.

[0004] The first aspect of this application provides a method for allocating sorting compartments in logistics, including: Determine the target logistics direction that needs to be allocated to the sorting grid in the logistics sorting scenario, and the number of grids that need to be allocated to the target logistics direction; Based on the grid allocation constraint information corresponding to the target logistics direction, a target allocation strategy is adopted to determine the target grids that meet the specified quantity in the candidate resource pool. The candidate resource pool includes static grids and spare grids. The static grids are grids configured with an unchangeable sorting plan. The target allocation strategy includes at least one of the following strategies: grid merging strategy and grid replenishment strategy. The grid merging strategy is used to merge static grids, and the grid replenishment strategy is used to select spare grids. The target compartment is assigned to the target logistics direction.

[0005] A second aspect of this application provides a logistics sorting compartment allocation device, comprising: The first determining module is used to determine the target logistics direction that needs to be allocated in the logistics sorting scenario, and the number of grids that need to be allocated corresponding to the target logistics direction. The second determining module is used to determine the target number of grid cells in the candidate resource pool based on the grid cell allocation constraint information corresponding to the target logistics direction and by adopting a target allocation strategy. The candidate resource pool includes static grid cells and spare grid cells. The static grid cells are grid cells configured with an unchangeable sorting plan. The target allocation strategy includes at least one of the following strategies: a grid cell merging strategy and a grid cell replenishment strategy. The grid cell merging strategy is used to merge static grid cells, and the grid cell replenishment strategy is used to select spare grid cells. The allocation module is used to allocate the target compartment to the target logistics direction.

[0006] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a logistics sorting compartment allocation method as described above.

[0007] The fourth aspect of this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a logistics sorting grid allocation method as described in any of the above.

[0008] The fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements a logistics sorting compartment allocation method as described in any of the above.

[0009] The logistics sorting grid allocation method of this application first determines the target logistics direction and the corresponding number of grids to be allocated in the logistics sorting scenario. Then, based on the grid allocation constraints corresponding to the target logistics direction, at least one of a grid merging strategy and a grid replenishment strategy is used to determine the target number of grids that meet the requirements from a candidate resource pool including static grids and spare grids. Finally, the target grids are allocated to the target logistics direction. In this application, by automatically determining the target grids from a candidate resource pool including static grids and spare grids using grid merging and replenishment strategies, there is no need for manual checking of multiple grids one by one, nor for manual judgment based on multiple allocation constraints. This allows for the rapid acquisition of an executable grid allocation scheme under the condition of a fixed number of grids, effectively improving grid allocation efficiency and thus solving the problem of low efficiency in manual grid reallocation in existing technologies. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a logistics sorting grid allocation method according to an embodiment of this application.

[0012] Figure 2 This is a structural block diagram of a logistics sorting grid distribution device shown in an embodiment of this application.

[0013] Figure 3 This is a schematic diagram of the physical structure of an electronic device as shown in an embodiment of this application. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0015] This application provides a method for allocating sorting grids in logistics, which effectively solves the problem of low efficiency in manual grid resource reallocation under the condition of a fixed number of sorting grids in existing technologies. The method can be implemented by electronic devices such as computers, servers, or logistics sorting scheduling equipment, or by a logistics sorting scheduling device installed in such electronic devices. This logistics sorting scheduling device can be implemented through software, hardware, or a combination of both. The following will describe the logistics sorting grid allocation method of this application in detail, taking logistics sorting scheduling equipment as the implementing entity.

[0016] Figure 1 This is a flowchart illustrating a logistics sorting grid allocation method according to an embodiment of this application. Figure 1 As shown, the logistics sorting compartment allocation method of this application includes: Step S101: Determine the target logistics direction that needs to be allocated to the sorting grid in the logistics sorting scenario, and the number of grids that need to be allocated to the target logistics direction.

[0017] In this embodiment, the logistics sorting scenario refers to the operational scenario in a logistics sorting center where sorting equipment is used to automatically sort packages according to their destination. Sorting equipment refers to equipment used for automated package sorting, such as cross-belt sorters, slider sorters, etc. Sorting equipment typically includes a conveyor belt and multiple slots set on both sides of the conveyor belt.

[0018] A sorting slot refers to the physical exit point on a sorting device used to guide packages from the conveyor belt to the collection container, which may be a collection bag or a cage cart. During the sorting process, packages are placed on the conveyor belt. After being scanned and identified, the sorting device ejects or slides the packages into the corresponding slots based on their destination. The collection container below the slot collects the packages in the corresponding logistics direction and packages them.

[0019] In this embodiment, the logistics direction (hereinafter referred to as flow direction) refers to the next node to which a package goes after leaving the current sorting center. Different logistics directions correspond to different package destinations. The logistics direction can be defined according to actual business needs. For example, the logistics direction can be a city-level node (e.g., sent to Shanghai), a specific sorting center (e.g., sent to the Shanghai Pudong sorting center), or a delivery outlet (e.g., sent to the Hangzhou West Lake branch). Within the same sorting center, one logistics direction corresponds to at least one compartment, and one compartment corresponds to at least one logistics direction. The collection container below the compartment is responsible for collecting packages corresponding to the logistics direction.

[0020] In this embodiment, the logistics sorting scenario can be represented by parameters such as date, location, and shift. The date represents the date on which the sorting operation occurs, such as June 3, 2026; the location represents the sorting center where the sorting operation is located, such as the Shenzhen sorting center; and the shift represents the working hours during which the sorting operation takes place, such as day shift (08:00-20:00) or night shift (20:00-08:00 the next day).

[0021] In this embodiment, when the load (i.e., the number of parcels or pieces) in a certain logistics direction exceeds the processing capacity of the slots already allocated to that logistics direction, additional slots need to be allocated to that logistics direction. Step S101 is used to determine which logistics directions need additional slots (i.e., determine the target logistics directions), and how many additional slots each target logistics direction needs to be allocated.

[0022] The number of storage spaces that need to be allocated for the target logistics direction does not include the number of storage spaces that already exist for that target logistics direction. In other words, the number of storage spaces that need to be allocated for the target logistics direction refers to the number of additional storage spaces that need to be allocated for that logistics direction.

[0023] In practice, the target logistics direction and the number of slots to be allocated can be determined based on the data on new package creation requirements. New package creation refers to a situation where, in the current logistics sorting scenario, the load of a certain logistics direction exceeds the processing capacity of the currently allocated slots, requiring additional slots to be allocated for package creation. Package creation involves placing new collection containers under the slots to collect packages in that logistics direction.

[0024] Step S102: Based on the grid allocation constraint information corresponding to the target logistics direction, adopt the target allocation strategy to determine the target number of grids that meet the requirements in the candidate resource pool. The candidate resource pool includes static grids and spare grids. Static grids are grids configured with an unchangeable sorting plan. The target allocation strategy includes at least one of the following strategies: grid merging strategy and grid replenishment strategy. The grid merging strategy is used to merge static grids, and the grid replenishment strategy is used to select spare grids.

[0025] In this embodiment, grid allocation constraint information refers to various constraint information related to grid allocation, including at least one of sorting scenario information, sorting equipment information, and sorting plan information. Specific grid allocation constraint information can be set according to actual needs.

[0026] Sorting scenario information includes the date, location, and shift, which is used to define the sorting operation scenario applicable to the grid allocation. For example, the date is June 3, 2026, the location is the Shenzhen sorting center, and the shift is the day shift.

[0027] Sorting equipment information includes the identifier of the line to which the sorting slot belongs. A line refers to an independent physical sorting unit on sorting equipment, consisting of a group of continuous slots. A sorting machine may include one or more lines. Each line has an independent conveyor belt and slot sequence. Slots on different lines are physically isolated from each other. Therefore, slots on different lines are usually not interchangeable; that is, a logistics direction can only use slots on the same line.

[0028] Sorting plan information includes plan identifier, plan version, timeliness requirements, logistics direction, and label attributes. The plan identifier is a unique number for the sorting plan, used to identify a set of sorting slot allocation rules; the plan version is the version number of the sorting plan, and the same plan identifier may exist in different versions at different times; the timeliness requirements refer to the time constraints for packages to be dispatched from the current sorting center and arrive at their destination, such as next-day delivery, three-day delivery, etc.; label attributes are business classification marks attached to the sorting slots or logistics directions, used to distinguish packages of different business types, such as general parcels, fresh parcels, and valuable parcels. Packages with different label attributes usually need to be sorted to different sorting slots.

[0029] In this embodiment, the target grid allocated to the target logistics direction needs to meet the grid allocation constraint information corresponding to the target logistics direction.

[0030] For example, if the target logistics direction is Shanghai, the corresponding sorting grid allocation constraints may include: sorting scenario information: June 3, 2026; Shenzhen sorting center; day shift; sorting equipment information: L1 line; sorting plan information: plan identifier SCH-008; plan version V3; delivery time requirement: next day; label attribute: ordinary item. In subsequent grid allocation processes, it is necessary to ensure that the additional target grids allocated to the Shanghai direction meet the above grid allocation constraints.

[0031] In this embodiment, the candidate resource pool refers to the set of all grids available for reallocation. The grids in the candidate resource pool may include static grids and spare grids.

[0032] Static sorting compartments are those configured with an unchangeable sorting plan. In other words, static sorting compartments have been pre-assigned to a fixed logistics direction, and this direction cannot be changed. For example, if compartment G012 is fixedly assigned to the Shanghai direction, then compartment G012 is a static sorting compartment.

[0033] The spare slot is a slot that can be assigned to a new logistics direction.

[0034] In this embodiment, the grid merging strategy is used to merge static grids in the candidate resource pool, transferring packages from at least one static grid to other static grids to free up the grid. The grid replenishment strategy is used to select an available grid from the spare grids in the candidate resource pool.

[0035] For example, suppose that during the daytime logistics sorting scenario at the Shenzhen sorting center on June 3, 2026, the load on the Shanghai direction increases sharply. Step S101 determines that 3 additional sorting slots need to be allocated to the Shanghai direction (this number does not include the 1 slot already allocated to the Shanghai direction, meaning there are 4 slots in total after allocation). In step S102, a slot merging strategy is first used to identify slots with lower loads from the static slots in the candidate resource pool. For example, if slot G045 currently has only 3 packages and slot G046 currently has only 5 packages, then the 3 packages from G045 can be transferred to G046, and slot G045 can be released as one of the target slots. If the number of target slots determined by the slot merging strategy is less than 3, a slot replenishment strategy is used to select available slots from the spare slots to supplement the remaining number until 3 target slots are determined.

[0036] Step S103: Assign the target compartment to the target logistics direction.

[0037] In this embodiment, the target compartment is assigned to the corresponding target logistics direction, so that the target compartment provides sorting services for that target logistics direction.

[0038] In this embodiment, the target logistics direction and the corresponding number of grids to be allocated in the logistics sorting scenario are first determined. Then, based on the grid allocation constraints corresponding to the target logistics direction, at least one of a grid merging strategy and a grid replenishment strategy is used to determine the target number of grids in a candidate resource pool including static grids and spare grids. Finally, the target grids are allocated to the target logistics direction. In this embodiment, by automatically determining the target grids from a candidate resource pool containing static grids and spare grids using grid merging and replenishment strategies, manual checking of multiple grid resources and judgment based on multiple allocation constraints are eliminated. This allows for rapid acquisition of an executable grid allocation scheme with a fixed number of grids, effectively improving grid allocation efficiency. Therefore, this application solves the problem of low efficiency in manual grid resource reallocation in the prior art.

[0039] In conjunction with the above embodiments, in one implementation, prior to step S101, this application may further include: Acquire multi-source data in logistics sorting scenarios. Multi-source data includes original new package creation demand data, original historical sorting operation data, original sorting plan data, original dynamic grid configuration data, and original idle grid data. The multi-source data is standardized to obtain preprocessed data, which includes new packaging demand data, historical sorting operation data, sorting plan data, dynamic grid configuration data, and idle grid data.

[0040] In this embodiment, multi-source data refers to data from different data sources.

[0041] Among them, the newly added packing demand data is used to characterize the logistics direction and demand intensity that require additional allocation of slots under specific dates, locations and shifts.

[0042] Historical sorting operation data is used to characterize the sorting type, load (number of pieces), line identification, plan identification, and plan version of each sorting slot. Each sorting slot is uniquely identified by its slot number.

[0043] Sorting plan data is used to characterize the relationship between sorting slots and logistics direction, logistics timeliness, and label attributes.

[0044] Dynamic grid configuration data is used to characterize the grid resources and their configuration information that can be switched between sorting plans.

[0045] Idle grid data is used to characterize grid resources that are not occupied by any sorting plan and their configuration information.

[0046] In this embodiment, since the multi-source data comes from different data sources, there may be inconsistencies in field representation between the data sources. Normalization processing refers to uniformly converting common fields in the multi-source data to eliminate the inconsistency in field representation between different data sources.

[0047] In practice, the objects of standardization include, but are not limited to, fields such as date, location, shift, grid number, plan identifier, and plan version. Standardization operations include at least one of the following: First, eliminate inconsistencies in the representation of null values, for example, unify "null", empty strings, and "N / A" as null value markers.

[0048] Second, eliminate inconsistent character formats, such as converting full-width characters to half-width characters and converting inconsistent uppercase and lowercase encodings to a unified uppercase format.

[0049] Third, remove leading and trailing spaces, for example, change "SZ001" to "SZ001".

[0050] In this embodiment, the target logistics direction and the number of slots to be allocated in the logistics sorting scenario can be determined based on the new packaging demand data and historical sorting operation data, which will be described in detail later.

[0051] In this embodiment, the grid allocation constraint information corresponding to the target logistics direction can be determined based on the newly added packaging demand data and the sorting plan data. Specifically, the newly added packaging demand data is used to determine the sorting scenario information in the grid allocation constraint information, and the sorting plan data is used to determine the sorting plan information and sorting equipment information in the grid allocation constraint information.

[0052] In this embodiment, a candidate resource pool can be constructed based on historical sorting operation data, sorting plan data, dynamic grid configuration data, and idle grid data. The candidate resource pool includes a static grid pool, a dynamic grid pool, and an idle grid pool.

[0053] The static sorting pool can be constructed based on historical sorting operation data and sorting plan data, and it contains all static sorting spaces in the current logistics sorting scenario. Low-load static sorting spaces are prioritized for retention as candidate resources to be released within the static sorting pool.

[0054] The dynamic grid pool can be built based on dynamic grid configuration data, and it contains all dynamic grids in the current logistics sorting scenario. The dynamic grid pool can be searched by date, location, shift, and line identifier to quickly retrieve dynamic grids that meet the requirements in the grid replenishment strategy.

[0055] The idle grid pool can be built based on idle grid data, containing all idle grids in the current logistics sorting scenario. The idle grid pool can be searched by date, location, and shift to quickly retrieve idle grids that meet the needs of the grid replenishment strategy. Since the idle grids are not currently bound to any production lines, the idle grid pool does not include the production line dimension.

[0056] In one implementation, this application can group static compartments in a static compartment pool according to logistics characteristics. Static compartments with identical logistics characteristics and capable of mutually accepting loads are grouped into the same compatible group. Information such as the number of compartments in each compatible group, the total load (total parcels / total pieces) within the group, and the compartment with the smallest load (parcels / pieces) is collected to facilitate subsequent implementation of a compartment merging strategy. The logistics characteristics include various information such as date, location, shift, line identification, plan identification, plan version, logistics timeliness, logistics direction, and label attributes, which can be specifically set according to actual needs.

[0057] In one implementation, the grid types in the candidate resource pool are not limited to static grids, dynamic grids, and idle grids, but can also be extended to other types of sorting processing units. Accordingly, grid merging strategies and grid replenishment strategies can also be adaptively adjusted for other types of sorting processing units.

[0058] In this embodiment, the grid cells in the candidate resource pool can be sorted from low to high load, or they can be sorted using a comprehensive scoring method. The comprehensive scoring method considers multiple factors such as the current load of each grid cell, the size of its compatibility group, and migration costs to determine the comprehensive score of each grid cell, and sorts them from high to low comprehensive scores, thereby prioritizing the grid cells with higher comprehensive scores for operation.

[0059] In this embodiment, standardizing multi-source data can eliminate the problem of inconsistent field definitions between different data sources, improve the quality of data required for logistics sorting grid allocation, and thus improve the efficiency and accuracy of subsequent grid allocation.

[0060] In conjunction with the above embodiments, in one implementation, step S101 may include: Step S1011: Obtain new package creation demand data and historical sorting operation data in the logistics sorting scenario. The new package creation demand data represents the load demand of each logistics direction in the logistics sorting scenario, and the historical sorting operation data represents the actual operating capacity of each compartment in the same historical logistics sorting scenario.

[0061] In this embodiment, the newly added package creation requirement data may include fields such as date, location, shift, logistics direction, and demand intensity. Among them, demand intensity can be represented by the expected package volume (expected piece volume), reflecting the number of packages that are expected to be processed in a certain logistics direction under the current logistics sorting scenario.

[0062] In this embodiment, historical sorting operation data is used to characterize the actual operational capacity of each sorting grid under similar historical logistics sorting scenarios. Similar historical logistics sorting scenarios refer to historical sorting scenarios that have the same scenario characteristics as the current logistics sorting scenario (i.e., the logistics sorting scenario in step S101). These scenario characteristics can be set according to actual needs, such as including location, shifts, etc.

[0063] Historical sorting operation data can include fields such as date, location, shift, grid number, grid type, load (number of items), line identifier, plan identifier, and plan version.

[0064] Step S1012: Based on the newly added package creation requirement data, determine the target logistics direction that needs to be allocated to the grid and the corresponding load requirement of the target logistics direction.

[0065] Step S1013: Determine the upper limit of the carrying capacity of a single compartment based on historical sorting operation data.

[0066] Step S1014: Determine the number of cells to be allocated for the target logistics direction based on the load requirements and the upper limit of the carrying capacity of a single cell.

[0067] In this embodiment, the load demand corresponding to the target logistics direction can be divided by the upper limit of the carrying capacity of a single grid, and the calculation result can be rounded up to obtain the number of grids that need to be allocated.

[0068] For example, assuming the load demand in the Shanghai direction is 5000 pieces, and the maximum capacity of a single compartment is 610 pieces, then the number of compartments needed is: rounded up (5000 ÷ 610) = rounded up (8.196) = 9 compartments. If there is already 1 compartment in the Shanghai direction, then an additional 9 - 1 = 8 compartments need to be allocated.

[0069] This embodiment can quantitatively calculate the number of compartments that need to be allocated in the target logistics direction, avoiding deviations caused by manual estimation based on experience, and ensuring the accuracy of the number of compartments.

[0070] In conjunction with the above embodiments, in one implementation, step S1012 may include: The logistics directions with load demand exceeding the load threshold in the newly added package creation demand data will be identified as the target logistics directions.

[0071] In this embodiment, the load threshold is a preset value, which can be determined based on experience.

[0072] In practice, when the load demand in a certain logistics direction exceeds the load threshold, that logistics direction can be identified as the target logistics direction that requires additional allocation of slots.

[0073] In one implementation, when there are multiple target logistics directions, steps S102 and S103 can be executed sequentially for each target logistics direction according to their load demand from high to low. By prioritizing the allocation of storage space to target logistics directions with higher load demand, it can be ensured that high-load logistics directions receive storage space resources first.

[0074] In addition to filtering by load threshold, a multi-indicator scoring method can also be used to comprehensively consider multiple indicators such as load demand, business priority of logistics direction and timeliness requirements, to score each logistics direction, and determine the logistics direction with a score higher than the preset score threshold as the target logistics direction.

[0075] In this embodiment, by setting a load threshold to filter logistics directions with low load demand, grid resources can be concentrated on high-load logistics directions that require additional grid allocation, avoiding unnecessary scheduling operations on low-load logistics directions and reducing resource consumption.

[0076] In conjunction with the above embodiments, in one implementation, step S1013 may include: Based on historical sorting operation data, determine the upper limit of the carrying capacity of a single compartment using any of the following methods: Method 1: Obtain the historical maximum load of static compartments in the target logistics sorting scenario from historical sorting operation data, and determine the larger value between the historical maximum load and the default load as the upper limit of the carrying capacity of a single compartment. The target logistics sorting scenario and the logistics sorting scenario belong to the same type of logistics sorting scenario.

[0077] In this approach, historical data for the target logistics sorting scenario is extracted from historical sorting operation data to obtain the historical maximum load of static compartments, i.e., the maximum number of packages that a single static compartment can handle in the target logistics sorting scenario. Then, the historical maximum load is compared with the default load, and the larger of the two is taken as the upper limit of the carrying capacity. The default load is a minimum load that can be set according to actual business needs.

[0078] Method 2: Obtain the historical load of static compartments in the target logistics sorting scenario from historical sorting operation data, and use the quantile value estimation method to determine the upper limit of the carrying capacity of a single compartment.

[0079] Quantile estimation involves sorting historical load data in ascending order and then taking the value at a specified percentile as the estimation result. For example, the 90th percentile of historical load data (i.e., 90% of historical load values ​​do not exceed this value) can be taken as the upper limit of carrying capacity. Compared to Method 1, which directly uses the historical maximum load or default load, quantile estimation can filter out the influence of extreme values ​​and obtain a more stable estimation result.

[0080] For example, in the historical sorting operation data, there are 100 load records for static grids. After sorting the loads from smallest to largest, the 90th value is 580 pieces, that is, the P90 percentile value is 580 pieces. Therefore, the upper limit of the carrying capacity is determined to be 580 pieces.

[0081] Method 3: Based on historical sorting operation data, a pre-trained load prediction model is used to determine the upper limit of the carrying capacity of a single compartment.

[0082] Among them, the load forecasting model can predict the upper limit of the carrying capacity of a single compartment based on the characteristics of the current logistics sorting scenario (such as whether the date is a weekday, whether it is during a peak business period, equipment operating status, etc.). Compared with the previous two methods, the load forecasting model can consider more influencing factors and obtain more accurate prediction results.

[0083] In this embodiment, if sufficient historical data is available, the upper limit of the carrying capacity can be obtained using quantile estimation; if abundant feature information is available, a load prediction model can be used; if limited data is available, the upper limit of the carrying capacity can be determined by combining the historical maximum load and the default load. This approach improves the flexibility and applicability of the upper limit of the carrying capacity estimation, thereby increasing the accuracy of the number of grid compartments.

[0084] In one implementation, in conjunction with the above embodiments, step S102 may include: According to the priority of each target allocation strategy from high to low, each target allocation strategy is adopted in turn to determine the target grid that meets the required number in the candidate resource pool.

[0085] In this embodiment, different strategies have different priorities, and the priority of each strategy can be set according to actual needs. For example, the priority of the grid merging strategy is higher than the priority of the grid replenishment strategy.

[0086] For example, if the target allocation strategy includes both a grid merging strategy and a grid replenishment strategy, and the priority of the grid merging strategy is higher than that of the grid replenishment strategy, then the target grid is first determined through the grid merging strategy. If the target grid that meets the quantity requirement cannot be obtained through the grid merging strategy, the remaining grids are replenished through the grid replenishment strategy until the target grid that meets the quantity requirement is obtained.

[0087] In one implementation, the grid merging strategy can be further divided into multiple sub-strategies, which can also have priorities. For example, the grid merging strategy can be divided into a multi-grid static merging strategy and a single-grid static merging strategy, with the priority of the multi-grid static merging strategy being higher than that of the single-grid static merging strategy.

[0088] In another implementation, the grid replenishment strategy can be further divided into multiple sub-strategies, which can also have priorities. For example, the grid replenishment strategy can be divided into a static-to-dynamic conversion strategy and an idle grid replenishment strategy, with the static-to-dynamic conversion strategy having a higher priority than the idle grid replenishment strategy.

[0089] The use of each of the above sub-strategies will be explained in detail later.

[0090] In this embodiment, by setting priorities for target allocation strategies and executing them sequentially in descending order of priority, strategies with lower execution costs can be prioritized for grid allocation, thereby reducing the execution cost of grid allocation and the impact on existing sorting operations while meeting grid allocation requirements.

[0091] In conjunction with the above embodiments, in one implementation, the grid merging strategy includes a multi-grid static merging strategy, which is used to merge the load of multiple static grids into one static grid. Based on this, step S102 may include: Step S1021A: When the target allocation strategy is a multi-grid static merging strategy, based on the grid allocation constraint information corresponding to the target logistics direction, determine the first compatible group in each compatible group in the candidate resource pool. The total load of each static grid in the first compatible group is not greater than the upper limit of the carrying capacity of a single static grid. The candidate resource pool manages each static grid in the form of compatible groups. A compatible group includes at least one static grid with the same logistics characteristics.

[0092] In this embodiment, different target allocation strategies can correspond to different allocation grid constraint information. If the target allocation strategy is a multi-grid static merging strategy, then the corresponding grid allocation constraint information can include multiple of the following: date, location, shift, identification of the line to which it belongs, plan identification, plan version, timeliness requirement, logistics direction, and label attribute. For example, the grid allocation constraint information corresponding to the multi-grid static merging strategy can be set to date, location, shift, identification of the line to which it belongs, plan identification, plan version, timeliness requirement, logistics direction, and label attribute to ensure that static grids within the same compatible group are consistent in all the above dimensions, thereby ensuring that the merging operation does not violate the actual operating conditions of the sorting operation.

[0093] In this embodiment, static grids within the same compatible group can share loads with each other, meaning that a package in one static grid can be transferred to another static grid within the same compatible group without violating grid allocation constraints.

[0094] In this embodiment, all packages in the static grids within the first compatible group can be merged into one static grid within the first compatible group, and the load of the merged static grid does not exceed the upper limit of its carrying capacity.

[0095] In one implementation, if there are multiple first compatible groups, a greedy heuristic selection strategy can be adopted to prioritize the first compatible group with the smallest total load within the group for merging operations, thereby reducing the cost of load transfer.

[0096] For example, assume the maximum carrying capacity is 610 pieces, and the target logistics direction is Shanghai. The compatible groupings in the candidate resource pool that satisfy the grid allocation constraints for the Shanghai direction are shown in Table 1 below: Compatible Groups Number of grids Total load within the group Line Information of each compartment within the group Is it the first compatible group? Group A 3 16 items L1 G045 (Lhasa direction, 3 items), G046 (Xining direction, 5 items), G047 (Yinchuan direction, 8 items) yes Group B 2 18 items L1 G102 (Haikou direction, 6 items), G103 (Sanya direction, 12 items) yes Group C 4 835 items L1 G060 (Fuzhou direction, 300 pieces), G061 (Xiamen direction, 280 pieces), G062 (Quanzhou direction, 250 pieces), G063 (Zhangzhou direction, 5 pieces) no Table 1 Within the same compatible group, all compartments have identical logistics characteristics, differing only in logistics direction and current load. Group A has a total load of 16 units, not exceeding 610 units, and Group B has a total load of 18 units, not exceeding 610 units; therefore, both Group A and Group B are first-compatibility groups. Group C has a total load of 835 units, exceeding 610 units, thus failing to meet the criteria and not being considered a first-compatibility group.

[0097] Following the greedy heuristic selection strategy, the first compatible group with the smallest total load within the group is selected first. Therefore, the processing order is: Group A, Group B.

[0098] Step S1022A: For each first compatible group, merge the load of each static grid in the first compatible group into one static grid in the first compatible group.

[0099] In this embodiment, for each first compatible group, one static compartment is selected as the receiving compartment, and the load of the remaining static compartments within the compatible group is transferred to this receiving compartment. In one implementation, the static compartment with the highest current load in the first compatible group can be selected as the receiving compartment to reduce the total number of packages that need to be transferred.

[0100] Following the example above, when performing a merge operation on group A, G047 (8 items) with the highest current load is selected as the receiving compartment. The 3 packages from G045 and the 5 packages from G046 are transferred to G047. The status of each compartment after the merge is shown in Table 2 below: Grid Before the merge load merged load state G045 3 0 Pending release G046 5 0 Pending release G047 8 16 Grid Table 2 Step S1023A: Determine the static grid with empty load in each of the first compatible groups after merging as the first grid, and the target grid includes the first grid.

[0101] In this embodiment, after the merging operation, the loads of all static grids in the first compatible group, except for the receiving grid, become empty. These static grids with empty loads are the first grids, which are part of the target grid.

[0102] Following the example above, after the merge is completed, the empty cells in group A are G045 and G046, and the empty cell in group B is G102. Therefore, the first cell is G045, G046, and G102, which is equivalent to releasing a total of 3 cells through the multi-cell static merging strategy.

[0103] In this embodiment, static grids are managed in the form of compatible groups, and a merge operation is performed on the first compatible group that meets the conditions, which can release multiple grids at once and improve grid release efficiency. In addition, by prioritizing the merging of compatible groups with the lowest total load within the group, the cost of load transfer can be reduced.

[0104] In conjunction with the above embodiments, in one implementation, the grid merging strategy includes a single-grid static merging strategy, which is used to transfer the load of a single static grid to another static grid. Based on this, step S102 includes: Step S1021B: When the target allocation strategy is a single-cell static merging strategy, based on the cell allocation constraint information corresponding to the target logistics direction, determine the second compatible group containing the static cell with the lowest current load in each compatible group in the candidate resource pool. The number of static cells contained in the second compatible group is greater than one.

[0105] In this embodiment, if the target allocation strategy is a single-cell static merging strategy, the corresponding cell allocation constraint information can include multiple of the following: date, location, shift, identification of the line to which it belongs, plan identification, plan version, timeliness requirement, logistics direction, and tag attribute. For example, the cell allocation constraint information corresponding to the single-cell static merging strategy can be set to date, location, shift, identification of the line to which it belongs, plan identification, plan version, timeliness requirement, logistics direction, and tag attribute to ensure that load transfer occurs between static cells with completely identical logistics characteristics.

[0106] In this embodiment, the single-cell static merging strategy is responsible for performing load transfer operations on the single static cell with the lowest current load in the candidate resource pool. Therefore, even if the total load within a compatible group exceeds the upper limit of its carrying capacity, as long as it contains the static cell with the lowest current load in the candidate resource pool, and the load of that static cell can be taken over by another static cell within the same compatible group, the static cell can be released through the single-cell static merging strategy.

[0107] In this embodiment, the second compatibility group needs to meet two conditions: first, it must contain the static grid with the lowest current load in the candidate resource pool; second, the number of static grids contained in the compatibility group must be greater than one.

[0108] In one implementation, a priority queue or equivalent sorting structure can be used to arrange the static grids in the candidate resource pool in ascending order of load, so as to quickly obtain the static grid with the lowest current load. A priority queue is a data structure in which elements are arranged according to priority, and the element with the highest priority (i.e., the lowest current load) is retrieved each time. Using the priority queue structure, the static grid with the lowest current load can be efficiently located even when the candidate resource pool is large.

[0109] For example, assuming the grid allocation constraints for a single-grid static merging strategy are the same as those for a multi-grid static merging strategy, and considering the aforementioned compatible grouping example, the multi-grid static merging strategy has been completed, with G045, G046, and G102 identified as the first grids, and G047 and G103 designated as receiving grids. The remaining compatible group in the candidate resource pool is group C, with a total load of 835 units, exceeding the maximum carrying capacity of 610 units. Therefore, the static grid with the lowest current load in the candidate resource pool is first obtained through a priority queue, which is assumed to be G063 in group C. Furthermore, group C contains four static grids (G060, G061, G062, and G063), a number greater than one, satisfying the condition for a second compatible group. Therefore, group C is designated as the second compatible group.

[0110] Step S1022B: In the second compatible group, the load of the static grid with the lowest current load is transferred to another static grid in the second compatible group, and the load of the other static grid after the transfer is not greater than the upper limit of the carrying capacity of a single static grid.

[0111] In this embodiment, within the second compatible group, another static cell capable of absorbing the load of the static cell with the lowest current load is found. The absorption condition is that the load of the other static cell after the transfer does not exceed the upper limit of its carrying capacity. If there are multiple static cells in the second compatible group that meet the absorption condition, any one of them can be selected as the absorption cell.

[0112] Following the example above, if G063 has a load of 5 items, then we need to find another static compartment in group C that can accept 5 packages. The acceptance determination process for each compartment in group C is as follows: G060 currently has a load of 300 units, and after acceptance, the load will be 305 units, not exceeding 610 units, which meets the condition; G061 currently has a load of 280 units, and after acceptance, the load will be 285 units, not exceeding 610 units, thus meeting the condition; G062 currently has a load of 250 units, and after acceptance, the load will be 255 units, not exceeding 610 units, thus meeting the requirements.

[0113] Therefore, all three compartments can accommodate the 5 packages in G063. Assuming G062 is used as the receiving compartment, the 5 packages in G063 need to be transferred to G062. After the transfer, the load of G062 will be 255 packages, and the load of G063 will become 0 packages. Therefore, G063 can be used as part of the second compartment.

[0114] Step S1023B: Repeat the above steps until a target number of grid cells is obtained, or the load of the static grid cell with the lowest current load in the candidate resource pool cannot be taken over by any other static grid cell in its compatibility group.

[0115] In this embodiment, each time steps S1021B to S1022B are executed, the load of the static grid with the lowest current load is transferred to another static grid within the same compatible group, making the load of that static grid zero. After one transfer is completed, the load distribution of each static grid in the candidate resource pool changes. At this time, steps S1021B to S1022B can be re-executed to continue searching for the next static grid with the lowest current load in the updated candidate resource pool and performing load transfer. The above process continues until any of the following termination conditions are met: First, the target number of cells has been obtained.

[0116] Second, the load of the non-empty static grid with the lowest current load in the candidate resource pool cannot be taken over by any other static grid in the same compatibility group. In other words, the load of the other static grid after the transfer will be greater than the upper limit of the carrying capacity.

[0117] Following the example above, after the first execution of steps S1021B to S1022B, the 5 packages in G063 have been transferred to G062, and the load of G063 becomes 0. At this time, the load of each compartment in group C is: G060 (300 packages), G061 (280 packages), G062 (255 packages), and G063 (0 packages).

[0118] Repeat step S1021B to obtain the static cell with the lowest current load from the candidate resource pool. Since the load of G063 is already 0 and it has been released, it will no longer participate in the subsequent load transfer operation. Among the remaining non-empty static cells, G062 (255 units) in group C is the static cell with the lowest current load, and group C to which G062 belongs contains two non-empty static cells, G060 and G061, which meets the conditions of the second compatible group.

[0119] Next, repeat step S1022B to find another static compartment in group C that can accept the 255 packages from G062. Since G061 currently has a load of 280 packages, the load after accepting the packages will be 280 + 255 = 535 packages, which is no more than 610 packages, thus satisfying the condition. Therefore, the 255 packages from G062 can be transferred to G061, making the load on G062 zero.

[0120] Continue repeating step S1021B: In group C, the non-empty static cell with the lowest current load is G060 (300 items). In group C to which G060 belongs, only G061 remains as a non-empty static cell. Since G061 currently has a load of 535 items, its load after the transfer will be 535 + 300 = 835 items, which is greater than 610 items, thus failing to meet the condition. Therefore, the transfer operation cannot continue, and the process ends.

[0121] Step S1024B: Determine the static grid with empty load in the second compatible group after the transfer as the second grid, and the target grid includes the second grid.

[0122] In this embodiment, after multiple rounds of transfer operations from step S1021B to step S1023B, there may be one or more static grids with empty loads in the second compatible group, and all of these static grids with empty loads can be determined as the second grid.

[0123] Following the example above, after two rounds of transfer operations, the loads of G063 and G062 in group C are both 0, so these two static grids can be identified as the second grid.

[0124] In this embodiment, by repeatedly executing steps S1021B to S1022B, static grids with lower loads can be released one by one within the same compatible group. Even if the total load within the compatible group exceeds the upper limit of the carrying capacity, multiple static grids can still be released gradually through multiple rounds of single-grid transfer, expanding the coverage of static grid release. Secondly, by using a priority queue structure to quickly obtain the static grid with the lowest current load in each round of transfer, the traversal range of invalid candidate static grids can be reduced, improving the efficiency of grid retrieval and matching.

[0125] In conjunction with the above embodiments, in one implementation, the spare sorting slot includes a dynamic sorting slot, which is a sorting slot configured with a variable sorting plan. The dynamic sorting slot can be switched from the current logistics direction to another logistics direction by modifying the configuration. The sorting slot replenishment strategy includes a static-to-dynamic transfer strategy, which is used to acquire dynamic sorting slots. Based on this, step S102 may include: Step S1021C: When the target allocation strategy is a static-to-dynamic acceptance strategy, based on the grid allocation constraint information corresponding to the target logistics direction, determine the dynamic grid as the third grid in the candidate resource pool, and the target grid includes the third grid.

[0126] In this embodiment, if the target allocation strategy is a static-to-dynamic switching strategy, the corresponding grid allocation constraint information can include multiple of the following: date, location, shift, identification of the line to which it belongs, plan identification, plan version, timeliness requirements, logistics direction, and label attributes. For example, the grid allocation constraint information corresponding to the static-to-dynamic switching strategy can be set to date, location, shift, and identification of the line to which it belongs. Since the sorting plan of the dynamic grid can be switched according to the configuration, there is no need to match the plan identification, plan version, etc.

[0127] In this embodiment, a static-to-dynamic assignment strategy can be adopted. Dynamic grids that meet the corresponding grid allocation constraints are searched from the dynamic grids in the candidate resource pool as the third grid. For example, dynamic grids that meet the requirements of date, location, shift, and line identifier and are in an available state can be retrieved from the dynamic grid pool of the candidate resource pool. As mentioned earlier, the dynamic grid pool has search keys established according to date, location, shift, and line identifier; therefore, dynamic grids that meet the requirements can be quickly located based on the search keys.

[0128] For example, suppose that after implementing the grid merging strategy, there are still 2 grids missing in the Shanghai direction. The grid allocation constraints for the Shanghai direction include a date of June 3, 2026, a location at the Shenzhen sorting center, a day shift, and a line identifier of L1. A query is performed in the dynamic grid pool using the search key 2026-06-03 / Shenzhen sorting center / day shift / L1. The query results are as follows: G150 is currently idle, which meets the requirements, and can be used as the third slot. G151 is currently occupied (allocated to another logistics direction) and does not meet the availability criteria. G152 is currently idle, which meets the requirements, and it can be used as the third slot.

[0129] Therefore, G150 and G152 can be designated as the third slot, filling in two slots.

[0130] In this embodiment, extending the grid allocation from static grids to dynamic grids can improve the success rate of grid allocation.

[0131] In conjunction with the above embodiments, in one implementation, the spare slots include idle slots, which are slots without any sorting plan configured, that is, neither a fixed nor a variable sorting plan is configured. The slot replenishment strategy includes an idle slot replenishment strategy, which is used to acquire idle slots. Based on this, step S102 may include: Step S1021D: When the target allocation strategy is the idle grid supplementation strategy, based on the grid allocation constraint information corresponding to the target logistics direction, an idle grid is determined as the fourth grid in the candidate resource pool, and the target grid includes the fourth grid.

[0132] In this embodiment, if the target allocation strategy is an idle grid replenishment strategy, the corresponding grid allocation constraint information can include multiple of the following: date, location, shift, identification of the line to which it belongs, plan identification, plan version, timeliness requirements, logistics direction, and label attributes. For example, the grid allocation constraint information corresponding to the idle grid replenishment strategy can be set to date, location, and shift. Since the idle grid is not currently bound to any line and has not been configured with any sorting plan, it is not necessary to match the identification of the line to which it belongs.

[0133] In this embodiment, an idle grid replenishment strategy can be adopted to obtain available idle grids that meet the corresponding grid allocation constraints from the idle grids in the candidate resource pool as the fourth grid. For example, idle grids that meet the requirements of date, location, and shift can be retrieved from the idle grid pool of the candidate resource pool.

[0134] For example, suppose that after implementing the grid merging strategy and the static-to-dynamic assignment strategy, there is still one grid slot short in the Shanghai direction. The grid allocation constraints for the Shanghai direction include a date of June 3, 2026, a location at the Shenzhen sorting center, and a day shift. A search in the idle grid slot pool using the search key "2026-06-03 / Shenzhen sorting center / day shift" yields the following results: G201 is currently not occupied by any sorting plan, meeting the demand, and can be used as the fourth sorting slot; G202 is currently not occupied by any sorting plan, meeting the demand, and can be used as the fourth sorting slot.

[0135] Therefore, G201 can be designated as the fourth gate, supplementing the one gate needed in the Shanghai direction.

[0136] In this embodiment, idle grids can be obtained from the idle grid pool of the candidate resource pool, and the resources allocated to the grids can be further extended to the idle grids, which can improve the success rate of grid allocation.

[0137] The grid allocation method of this application will be described below with a complete embodiment. In this embodiment, the target allocation strategy includes a multi-grid static merging strategy, a single-grid static merging strategy, a static-to-dynamic acceptance strategy, and an idle grid replenishment strategy, and are ordered from high to low priority as follows: multi-grid static merging strategy, single-grid static merging strategy, static-to-dynamic acceptance strategy, and idle grid replenishment strategy. Assuming the target logistics direction is Shanghai, the number of grids to be allocated corresponding to the target logistics direction is 6, the maximum carrying capacity is 610 pieces, and the line body identifier in the grid allocation constraint information is L1, then the process of determining the 6 target grids is as follows: The first step is to execute the multi-cell static merging strategy. The compatible groups in the candidate resource pool that satisfy the cell allocation constraints include: Group A: Includes G045 (3 pieces), G046 (5 pieces), and G047 (8 pieces), with a total load of 16 pieces in the group; Group B: Includes G102 (6 pieces) and G103 (12 pieces), with a total load of 18 pieces in the group; Group C: Includes G060 (300 pieces), G061 (280 pieces), G062 (250 pieces), and G063 (5 pieces), with a total load of 835 pieces in the group.

[0138] Among them, the total load within Group A and Group B is no greater than the upper limit of the bearing capacity of 610 units, thus meeting the static merging condition for multiple compartments. The total load within Group C, 835 units, is greater than 610 units, and therefore does not meet the condition.

[0139] For Group A, perform a merge: merge the loads of G045 (3 units) and G046 (5 units) into G047. After the merge, G047 will have a load of 16 units. Release G045 and G046. For Group B, perform a merge: merge the load of G102 (6 units) into G103. After the merge, G103 will have a load of 18 units. Release G102. The multi-cell static merging strategy releases a total of 3 cells (G045, G046, and G102). These 3 cells are designated as the first cells. At this point, there are still 3 cells missing.

[0140] The second step is to execute the single-cell static merging strategy. The static cell with the lowest current load in the candidate resource pool is identified as G063 (5 units) through a priority queue. Group C, to which G063 belongs, contains 4 static cells, satisfying the conditions for the second compatible group. The 5 units of load from G063 are transferred to G062. After the transfer, the load of G062 is 255 units, and the load of G063 becomes 0. G063 is then released.

[0141] Continue to obtain the non-empty static grid with the lowest current load as G062 (255 units). Transfer the 255 units load of G062 to G061. After the transfer, the load of G061 is 535 units, and the load of G062 becomes 0. Release G062.

[0142] The current non-empty static cell with the lowest load is identified as G060 (300 units). The 300 units load of G060 are transferred to G061. After the transfer, the load of G061 will be 835 units, which is greater than 610 units, making further transfer impossible. The single-cell static merging strategy ends. The single-cell static merging strategy released two cells (G063 and G062), which are designated as the second cell. At this point, one cell is still needed.

[0143] The third step is to execute the static-to-dynamic conversion strategy. Based on the search key "2026-06-03 / Shenzhen Sorting Center / Day Shift / L1", a search was conducted in the dynamic grid pool. No available dynamic grids were found, indicating that the static-to-dynamic conversion strategy failed to acquire a grid; one grid is still needed.

[0144] The fourth step is to implement the idle slot replenishment strategy. Based on the search key "2026-06-03 / Shenzhen Sorting Center / Day Shift", the idle slot pool is searched. G201 is found to be an available idle slot and is designated as the fourth slot. Currently, six target slots have been obtained, meeting the quantity requirement.

[0145] In summary, by sequentially executing the multi-grid static merging strategy, the single-grid static merging strategy, the static-to-dynamic conversion strategy, and the idle grid supplementation strategy, a total of 6 target grids were obtained: the first grids are G045, G046, and G102; the second grids are G063 and G062; and the fourth grid is G201. Finally, these 6 target grids were allocated to the Shanghai direction.

[0146] In conjunction with the above embodiments, in one implementation, the method of this application may further include: If the target allocation strategy cannot determine the number of target cells that meet the requirements, an anomaly diagnosis result is generated based on the cell allocation constraint information and the candidate resource pool configuration information. The anomaly diagnosis result is used to indicate the reason why the target cells were not hit.

[0147] In this embodiment, if the target grid allocation strategy fails to obtain the required number of grid cells after execution, the system enters the anomaly diagnosis phase. The purpose of anomaly diagnosis is to analyze the specific reasons for grid cell allocation failures, so that maintenance personnel can quickly locate the problem and take corresponding measures based on the diagnostic results.

[0148] In practice, the anomaly diagnosis process includes the following steps: First, based on the date, location, and shift in the grid allocation constraint information, determine the sorting plan version corresponding to the current logistics sorting scenario, and establish a mapping relationship between the plan version and the plan identifier.

[0149] Next, combining the grid allocation constraint information and the candidate resource pool configuration information (including dynamic grid configuration data, sorting plan data, etc.), the reasons for the missed sorting are investigated item by item, and anomaly diagnosis results are generated. Anomaly diagnosis results include at least one of the following: First, no corresponding plan version was found. This means that no sorting plan version matching the current logistics sorting scenario was found in the sorting plan data, making it impossible to establish a mapping relationship between the plan version and the plan identifier. Subsequent strategies cannot be executed due to the lack of an effective plan association.

[0150] Second, dynamic grids are not configured. Specifically, no dynamic grid record matching the current logistics sorting scenario was found in the dynamic grid configuration data, resulting in no available dynamic grid resources for the static-to-dynamic conversion strategy.

[0151] Third, dynamic grids have been configured but the constraints are not met. That is, there is a dynamic grid record in the dynamic grid configuration data that matches the current logistics sorting scenario, but the dynamic grid does not meet other constraints in the grid allocation constraint information (such as line identifier mismatch, plan identifier mismatch, etc.), which makes the dynamic grid unselectable.

[0152] In one implementation, abnormal diagnostic results may also include, but are not limited to, the following: Line mismatch means that the available grids in the candidate resource pool are inconsistent with the line identifier required by the target logistics direction; Insufficient capacity means that the number of available grid cells in the candidate resource pool is insufficient to meet the allocation requirements.

[0153] In this embodiment, by automatically generating abnormal diagnostic results when the target allocation strategy cannot meet the allocation requirements, the reasons for the grid allocation failure can be presented to the operation and maintenance personnel in a structured manner, avoiding manual item-by-item investigation by the operation and maintenance personnel and improving the efficiency of problem localization.

[0154] In conjunction with the above embodiments, in one implementation, after step S103, the method of this application may further include: Each target cell in the candidate resource pool, and the cell used to take on loads during the execution of the cell merging strategy, are marked as locked. The locked state indicates that the cell cannot be used for cell allocation in other logistics directions.

[0155] In this embodiment, after the target grid is assigned to the target logistics direction, the candidate resource pool needs to be updated to mark the grid involved in this grid assignment process as locked to prevent the grid assignment process of other logistics directions from occupying the already assigned grid resources again.

[0156] In this embodiment, the grids that need to be marked as locked include target grids and receiving grids. A receiving grid is a static grid that, during the execution of the grid merging strategy, takes over the load of other static grids. Although the receiving grid has not been assigned to the target logistics direction, its load has increased due to the merging operation, and its remaining carrying capacity has changed. Marking it as locked can prevent subsequent allocation processes from repeatedly operating on the receiving grid based on outdated load information.

[0157] In practice, the state update operation includes at least one of the following: First, mark the released static grids in the static grid pool (i.e., the static grids in the target grid) as locked.

[0158] Second, mark the static grids in the static grid pool that have been designated as receiving objects as locked.

[0159] Third, mark the selected dynamic grids in the dynamic grid pool (i.e., the dynamic grids in the target grid) as locked.

[0160] Fourth, mark the selected idle grids in the idle grid pool (i.e., the idle grids in the target grid) as locked.

[0161] In one implementation, in addition to marking the status of each target grid in the candidate resource pool and the receiving grid used to take over the load during the execution of the grid merging strategy as locked, the aforementioned grids can also be removed from the sub-pools corresponding to the candidate resource pool. Specifically, static grids in the target grids are removed from the static grid pool, static grids that are the receiving objects are removed from the static grid pool, dynamic grids in the target grids are removed from the dynamic grid pool, and idle grids in the target grids are removed from the idle grid pool. By directly removing the allocated grids from the candidate resource pool, the size of the candidate resource pool can be reduced, and the retrieval overhead in the subsequent grid allocation process can be reduced.

[0162] In this embodiment, by locking the status of the target grid and the receiving grid after the grid allocation is completed, it can be ensured that the grid status in the candidate resource pool is consistent with the actual allocation result, avoiding the repeated occupation of the allocated grid resources in the subsequent grid allocation process of other logistics directions, and ensuring that the grid allocation results between multiple logistics directions do not conflict with each other.

[0163] In this embodiment, after assigning the target grid to the target logistics direction, the method of this application can also output grid assignment result information, which includes at least one of the following: First, the identification information for newly added packaging requirements includes the date, location, shift, and logistics direction corresponding to the target logistics direction, which is used to identify the logistics sorting scenario and target logistics direction corresponding to this grid allocation.

[0164] Second, the number of storage spaces to be allocated, that is, the number of additional storage spaces that need to be allocated for the target logistics direction.

[0165] Third, the identification information of the target grid and the identification information of the receiving grid. The identification information of the target grid includes the grid number of each target grid, and the identification information of the receiving grid includes the grid number of each receiving grid and the load it will bear.

[0166] Fourth, the plan identifier and plan version corresponding to the target compartment are used to record the sorting plan associated with this compartment allocation.

[0167] Fifth, the type of target allocation strategy that was hit, that is, the type of strategy that was actually executed and successfully obtained the target grid during this grid allocation process, such as multi-grid static merging strategy, single-grid static merging strategy, static to dynamic takeover strategy, or idle grid supplementation strategy.

[0168] Sixth, anomaly diagnosis results. When the target allocation strategy cannot determine the number of target cells that meet the requirements, anomaly diagnosis results are output to indicate the reason why the target cells were not hit.

[0169] By outputting the grid allocation results, the system can provide maintenance personnel with a complete record of grid allocation execution, making it easier for them to verify and trace the grid allocation results.

[0170] In summary, the method of this application has at least the following technical effects: First, for the problem that the number of physical slots in the logistics sorting scenario is fixed and cannot be quickly coped with high-load logistics directions by temporarily adding hardware, this application adopts a slot merging strategy to release slots by merging low-load static slots in a candidate resource pool containing static slots and spare slots, and adopts a slot replenishment strategy to obtain available slots from spare slots. Under the condition that the number of physical slots is fixed, it can automatically determine the available target slots and allocate them to the target logistics direction. There is no need to manually check various slot resources one by one, which can effectively solve the problem of low efficiency of manual redistribution of slot resources in the prior art.

[0171] Secondly, when additional grid slots are needed for high-load logistics directions, existing solutions struggle to quickly identify and release available grid resources from already occupied low-load slots. This application addresses this by employing a priority queue or equivalent sorting structure to arrange static grids in the candidate resource pool in ascending order of load. Based on compatible grouping constraints, it prioritizes merging static grids with the lowest load under conditions such as date, location, shift, line identifier, plan identifier, and plan version. This enables rapid retrieval and matching of low-load grids, reduces the traversal range of invalid candidate grids, and thus solves the problem of low efficiency in identifying and releasing low-load grids.

[0172] Third, regarding the problem that sorting operation data, sorting plan data, dynamic grid configuration data, and idle grid data are scattered across different data sources, have inconsistent field definitions, and are difficult to form a unified candidate resource pool, this application standardizes common fields such as date, location, shift, grid number, plan identifier, and plan version in multi-source data. This eliminates problems such as inconsistent null value representation, inconsistent character format, and leading and trailing spaces between different data sources. Based on the preprocessed data, a candidate resource pool containing a static grid pool, a dynamic grid pool, and an idle grid pool is constructed. This can transform scattered multi-source data into a unified candidate resource pool, improve the consistency of association between different data sources, and thus solve the problem of inconsistent definitions in multi-source data leading to the inability to uniformly schedule data.

[0173] Fourth, regarding the problem of low efficiency and easy omission of constraints in manual analysis when multiple constraints such as date, location, shift, line identification, plan identification, plan version, and compatible grouping exist simultaneously, this application automatically matches grids that meet all constraints from the candidate resource pool by allocating constraint information (including sorting scenario information, sorting equipment information, and sorting plan information) according to the grid allocation constraint information corresponding to the target logistics direction. This enables automatic grid matching under multiple constraints, improves the consistency between grid allocation results and actual sorting operation conditions, and thus solves the problem of low efficiency and easy omission when manually allocating grids under multiple constraints.

[0174] Fifth, regarding the lack of a hierarchical scheduling mechanism for static, dynamic, and idle grids, this application prioritizes target allocation strategies and executes them sequentially in the order of multi-grid static merging strategy, single-grid static merging strategy, static-to-dynamic conversion strategy, and idle grid supplementation strategy. This enables systematic hierarchical scheduling of different types of grid resources, prioritizing strategies with lower execution costs. While meeting grid allocation requirements, it reduces the impact on existing sorting operations, thereby solving the problem of insufficient utilization of grid resources due to the lack of a hierarchical scheduling mechanism.

[0175] Sixth, regarding the lack of dynamic status updates for released grids and grids that have taken on loads, which can easily lead to the same grid being repeatedly allocated, this application addresses the issue of marking the target grid and the receiving grid as locked or removing them from the candidate resource pool after grid allocation. This enables dynamic status updates for allocated grid resources, ensuring that the grid status in the candidate resource pool remains consistent with the actual allocation results, thereby resolving the problem of grids being repeatedly allocated due to the lack of a status update mechanism.

[0176] Seventh, regarding the problem that it is difficult to accurately estimate the carrying capacity of a single compartment based on historical data, thus affecting the accuracy of the calculation of the number of compartments required, this application determines the upper limit of the carrying capacity of a single compartment by using various methods such as taking the larger value between the historical maximum load and the default load, quantile value estimation, or load prediction models based on historical sorting operation data. This can realize the automatic calculation of the number of compartments to be allocated based on historical carrying capacity, improve the stability and accuracy of the estimation of the number of compartments required, and thus solve the problem of inaccurate estimation of the number of compartments required.

[0177] Eighth, regarding the lack of an automatic analysis mechanism for the reasons for missed allocation when the target allocation strategies cannot meet the grid allocation requirements, which leads to maintenance personnel having to manually check each item, this application generates structured anomaly diagnosis results based on grid allocation constraint information and candidate resource pool configuration information. It distinguishes different reasons such as missing plan version, unconfigured dynamic grid, and unmet constraints, which can realize automated problem diagnosis in missed scenarios, improve the accuracy and efficiency of problem location, and thus solve the problem of low efficiency in manual investigation of missed reasons by maintenance personnel.

[0178] The following describes a logistics sorting grid allocation device provided in this application. The logistics sorting grid allocation device described below can be referred to in correspondence with the logistics sorting grid allocation method described above.

[0179] Figure 2 This is a structural block diagram of a logistics sorting grid distribution device shown in an embodiment of this application. Figure 2 As shown, the logistics sorting compartment distribution device 200 of this application may include: The first determining module 201 is used to determine the target logistics direction that needs to be allocated in the logistics sorting scenario, and the number of grids that need to be allocated corresponding to the target logistics direction. The second determining module 202 is used to determine the target number of grid cells in the candidate resource pool according to the grid cell allocation constraint information corresponding to the target logistics direction and by adopting a target allocation strategy. The candidate resource pool includes static grid cells and spare grid cells. The static grid cells are grid cells configured with an unchangeable sorting plan. The target allocation strategy includes at least one of the following strategies: grid cell merging strategy and grid cell replenishment strategy. The grid cell merging strategy is used to merge static grid cells, and the grid cell replenishment strategy is used to select spare grid cells. The allocation module 203 is used to allocate the target compartment to the target logistics direction.

[0180] According to the logistics sorting grid allocation device 200 provided in this application, the second determining module 202 is used to: sequentially adopt each of the target allocation strategies in descending order of priority, and determine the target grids that meet the specified number in the candidate resource pool.

[0181] According to the logistics sorting grid allocation device 200 provided in this application, the grid merging strategy includes a multi-grid static merging strategy, which is used to merge the load of multiple static grids into one static grid. The second determining module 202 is used to: when the target allocation strategy is the multi-grid static merging strategy, determine a first compatible group in each compatible group in the candidate resource pool according to the grid allocation constraint information corresponding to the target logistics direction, wherein the total load of each static grid in the first compatible group is not greater than the upper limit of the carrying capacity of a single static grid, wherein the candidate resource pool manages each static grid in the form of compatible groups, and a compatible group includes at least one static grid with the same logistics characteristics; for each first compatible group, merge the load of each static grid in the first compatible group into one static grid in the first compatible group; and determine the static grid with no load in each first compatible group after merging as the first grid, wherein the target grid includes the first grid.

[0182] According to the logistics sorting grid allocation device 200 provided in this application, the grid merging strategy includes a single-grid static merging strategy, which is used to transfer the load of a single static grid to another static grid. The second determining module 202 is used to: when the target allocation strategy is the single-grid static merging strategy, determine a second compatible group containing the static grid with the lowest current load in each compatible group in the candidate resource pool according to the grid allocation constraint information corresponding to the target logistics direction; the second compatible group contains more than one static grid; in the second compatible group, transfer the load of the static grid with the lowest current load to another static grid in the second compatible group, and the load of the other static grid after the transfer is not greater than the upper limit of the carrying capacity of a single static grid; repeat the above steps until a target grid that meets the specified number is obtained, or the load of the non-empty static grid with the lowest current load in the candidate resource pool cannot be taken over by any other static grid in its compatible group; determine the static grid with an empty load in the second compatible group after the transfer as the second grid, and the target grid includes the second grid.

[0183] According to the logistics sorting grid allocation device 200 provided in this application, the spare grid includes a dynamic grid, which is a grid configured with a variable sorting plan. The grid replenishment strategy includes a static-to-dynamic acceptance strategy, which is used to obtain a dynamic grid. The second determining module 202 is used to: determine a dynamic grid as a third grid in the candidate resource pool according to the grid allocation constraint information corresponding to the target logistics direction when the target allocation strategy is the static-to-dynamic acceptance strategy. The target grid includes the third grid.

[0184] According to the logistics sorting grid allocation device 200 provided in this application, the spare grid includes an idle grid, which is a grid without any sorting plan configured. The grid replenishment strategy includes an idle grid replenishment strategy, which is used to obtain idle grids. The second determining module 202 is used to: when the target allocation strategy is the idle grid replenishment strategy, determine an idle grid as a fourth grid in the candidate resource pool according to the grid allocation constraint information corresponding to the target logistics direction. The target grid includes the fourth grid.

[0185] According to the logistics sorting grid allocation device 200 provided in this application, the first determining module 201 is used to: acquire new packaging demand data and historical sorting operation data in the logistics sorting scenario, wherein the new packaging demand data represents the load demand of each logistics direction in the logistics sorting scenario, and the historical sorting operation data represents the actual operating capacity of each grid in the same historical logistics sorting scenario; determine the target logistics direction to be allocated grids and the load demand corresponding to the target logistics direction based on the new packaging demand data; determine the upper limit of the carrying capacity of a single grid based on the historical sorting operation data; and determine the number of grids to be allocated corresponding to the target logistics direction based on the load demand and the upper limit of the carrying capacity of a single grid.

[0186] According to the logistics sorting grid allocation device 200 provided in this application, the first determining module 201 is used to: determine the logistics direction in the newly added packaging demand data where the load demand is higher than the load threshold as the target logistics direction.

[0187] According to the logistics sorting grid allocation device 200 provided in this application, the first determining module 201 is used to: determine the upper limit of the carrying capacity of a single grid according to the historical sorting operation data, using any one of the following methods: obtaining the historical maximum load of the static grid in the target logistics sorting scenario in the historical sorting operation data, and determining the maximum value between the historical maximum load and the default load as the upper limit of the carrying capacity of the single grid, wherein the target logistics sorting scenario and the logistics sorting scenario belong to the same type of logistics sorting scenario; obtaining the historical load of the static grid in the target logistics sorting scenario in the historical sorting operation data, and determining the upper limit of the carrying capacity of the single grid using the quantile estimation method; and determining the upper limit of the carrying capacity of the single grid using a pre-trained load prediction model based on the historical sorting operation data.

[0188] The logistics sorting grid allocation device 200 provided in this application further includes an anomaly module, which is used to: generate an anomaly diagnosis result based on the grid allocation constraint information and the configuration information of the candidate resource pool when the target allocation strategy cannot determine the target grid that meets the specified number of grids. The anomaly diagnosis result is used to indicate the reason why the target grid was not matched.

[0189] The logistics sorting grid allocation device 200 provided in this application further includes a marking module, which is used to mark the status of each target grid in the candidate resource pool and the receiving grid used to take on the load during the execution of the grid merging strategy as locked, wherein the locked status indicates that the grid cannot be used for allocation in other logistics directions.

[0190] Figure 3This is a schematic diagram of the physical structure of an electronic device shown in an embodiment of this application, such as... Figure 3 As shown, the electronic device may include a processor 310, a communications interface 320, a memory 330, and a communication bus 340. The processor 310, communications interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions stored in the memory 330 to execute a logistics sorting grid allocation method.

[0191] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0192] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute a logistics sorting grid allocation method provided by the above methods.

[0193] In another aspect, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform a logistics sorting grid allocation method provided by the methods described above.

[0194] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0195] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0196] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for allocating sorting compartments in logistics, characterized in that, include: Determine the target logistics direction that needs to be allocated to the sorting grid in the logistics sorting scenario, and the number of grids that need to be allocated to the target logistics direction; Based on the grid allocation constraint information corresponding to the target logistics direction, a target allocation strategy is adopted to determine the target grids that meet the specified quantity in the candidate resource pool. The candidate resource pool includes static grids and spare grids. The static grids are grids configured with an unchangeable sorting plan. The target allocation strategy includes at least one of the following strategies: grid merging strategy and grid replenishment strategy. The grid merging strategy is used to merge static grids, and the grid replenishment strategy is used to select spare grids. The target compartment is assigned to the target logistics direction.

2. The logistics sorting grid allocation method according to claim 1, characterized in that, The step of employing a target allocation strategy to determine the target number of cells that meet the specified quantity from the candidate resource pool includes: According to the priority of each target allocation strategy from high to low, each target allocation strategy is applied sequentially to determine the target grid that meets the specified number in the candidate resource pool.

3. The logistics sorting grid allocation method according to claim 1, characterized in that, The grid merging strategy includes a multi-grid static merging strategy, which is used to merge the load of multiple static grids into one static grid. The step of determining the target number of target grids from the candidate resource pool based on the grid allocation constraint information corresponding to the target logistics direction and using a target allocation strategy includes: When the target allocation strategy is the multi-grid static merging strategy, according to the grid allocation constraint information corresponding to the target logistics direction, a first compatible group is determined in each compatible group in the candidate resource pool. The total load of each static grid in the first compatible group is not greater than the upper limit of the carrying capacity of a single static grid. The candidate resource pool manages each static grid in the form of compatible groups. A compatible group includes at least one static grid with the same logistics characteristics. For each of the first compatible groups, the load of each static grid in the first compatible group is merged into one static grid in the first compatible group; The static grid with no load in each of the first compatible groups after merging is determined as the first grid, and the target grid includes the first grid.

4. The logistics sorting grid allocation method according to claim 1, characterized in that, The grid merging strategy includes a single-grid static merging strategy, which is used to transfer the load of a single static grid to another static grid. The step of determining the target number of target grids in the candidate resource pool based on the grid allocation constraint information corresponding to the target logistics direction and using a target allocation strategy includes: When the target allocation strategy is the single-cell static merging strategy, based on the cell allocation constraint information corresponding to the target logistics direction, a second compatible group containing the static cell with the lowest current load is determined in each compatible group in the candidate resource pool, and the number of static cells contained in the second compatible group is greater than one. In the second compatible group, the load of the static grid with the lowest current load is transferred to another static grid in the second compatible group, and the load of the other static grid after the transfer is not greater than the upper limit of the carrying capacity of a single static grid. Repeat the above steps until the target number of grid cells is obtained, or the load of the non-empty static grid cell with the lowest current load in the candidate resource pool cannot be taken over by any other static grid cell in the same compatibility group. The static grid with an empty load in the second compatible group after the transfer is identified as the second grid, and the target grid includes the second grid.

5. The logistics sorting grid allocation method according to claim 1, characterized in that, The spare slots include dynamic slots, which are slots configured with variable sorting plans. The slot replenishment strategy includes a static-to-dynamic conversion strategy, which is used to acquire dynamic slots. The step of determining the target number of target slots in the candidate resource pool based on the slot allocation constraint information corresponding to the target logistics direction and using a target allocation strategy includes: When the target allocation strategy is the static-to-dynamic acceptance strategy, a dynamic grid is determined as the third grid in the candidate resource pool based on the grid allocation constraint information corresponding to the target logistics direction, and the target grid includes the third grid.

6. The logistics sorting grid allocation method according to claim 1, characterized in that, The spare slots include idle slots, which are slots without any sorting plans configured. The slot replenishment strategy includes an idle slot replenishment strategy, which is used to acquire idle slots. The step of determining the target number of target slots in the candidate resource pool based on the slot allocation constraint information corresponding to the target logistics direction, using a target allocation strategy, includes: When the target allocation strategy is the idle grid replenishment strategy, an idle grid is determined as the fourth grid in the candidate resource pool according to the grid allocation constraint information corresponding to the target logistics direction, and the target grid includes the fourth grid.

7. The logistics sorting grid allocation method according to claim 1, characterized in that, The determination of the target logistics direction that needs to be allocated to the sorting grid in the logistics sorting scenario, and the number of grids that need to be allocated corresponding to the target logistics direction, includes: Acquire new packaging demand data and historical sorting operation data in the logistics sorting scenario. The new packaging demand data represents the load demand of each logistics direction in the logistics sorting scenario, and the historical sorting operation data represents the actual operating capacity of each compartment in the same historical logistics sorting scenario. Based on the newly added package creation requirement data, determine the target logistics direction that needs to be allocated to the grid, and the load requirement corresponding to the target logistics direction; Based on the historical sorting operation data, determine the upper limit of the carrying capacity of a single compartment; Based on the load demand and the upper limit of the carrying capacity of a single compartment, determine the number of compartments that need to be allocated for the target logistics direction.

8. The logistics sorting grid allocation method according to claim 7, characterized in that, The step of determining the target logistics direction for allocating storage compartments based on the newly added packaging demand data includes: The logistics directions in the newly added package creation demand data where the load demand is higher than the load threshold are identified as the target logistics directions.

9. The logistics sorting grid allocation method according to claim 7, characterized in that, The step of determining the upper limit of the carrying capacity of a single compartment based on the historical sorting operation data includes: Based on the historical sorting operation data, determine the upper limit of the carrying capacity of a single compartment using any of the following methods: Obtain the historical maximum load of the static compartment in the target logistics sorting scenario from the historical sorting operation data, and determine the maximum value between the historical maximum load and the default load as the upper limit of the carrying capacity of the single compartment. The target logistics sorting scenario and the logistics sorting scenario belong to the same type of logistics sorting scenario. Obtain the historical load of the static compartments in the target logistics sorting scenario from the historical sorting operation data, and determine the upper limit of the carrying capacity of the individual compartment using the quantile value estimation method; Based on the historical sorting operation data, a pre-trained load prediction model is used to determine the upper limit of the carrying capacity of the individual compartment.

10. The logistics sorting grid allocation method according to claim 1, characterized in that, Also includes: If the target allocation strategy fails to determine the required number of target cells, an anomaly diagnosis result is generated based on the cell allocation constraint information and the configuration information of the candidate resource pool. The anomaly diagnosis result is used to indicate the reason why the target cells were not hit.

11. The logistics sorting grid allocation method according to claim 1, characterized in that, After assigning the target compartment to the target logistics direction, the method further includes: The status of each target grid in the candidate resource pool and the receiving grid used to take on the load during the execution of the grid merging strategy are marked as locked, and the locked status indicates that the grid cannot be used for grid allocation in other logistics directions.

12. A logistics sorting grid distribution device, characterized in that, include: The first determining module is used to determine the target logistics direction that needs to be allocated in the logistics sorting scenario, and the number of grids that need to be allocated corresponding to the target logistics direction. The second determining module is used to determine the target number of grid cells in the candidate resource pool based on the grid cell allocation constraint information corresponding to the target logistics direction and by adopting a target allocation strategy. The candidate resource pool includes static grid cells and spare grid cells. The static grid cells are grid cells configured with an unchangeable sorting plan. The target allocation strategy includes at least one of the following strategies: a grid cell merging strategy and a grid cell replenishment strategy. The grid cell merging strategy is used to merge static grid cells, and the grid cell replenishment strategy is used to select spare grid cells. The allocation module is used to allocate the target compartment to the target logistics direction.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements a logistics sorting grid allocation method as described in any one of claims 1 to 12.

14. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a logistics sorting grid allocation method as described in any one of claims 1 to 12.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements a logistics sorting grid allocation method as described in any one of claims 1 to 12.

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