Method and apparatus for optimizing sorting plan, and electronic device and storage medium

Abstract

A method for optimizing a sorting plan. The method comprises: after a sorting efficiency parameter of an initial sorting plan is acquired, adjusting the initial sorting plan according to the sorting efficiency parameter of the initial sorting plan, so as to obtain an intermediate sorting plan corresponding to the initial sorting plan; performing sorting simulation on the intermediate sorting plan by means of a digital twin, so as to obtain a sorting efficiency parameter of the intermediate sorting plan; and repeating in this way, and obtaining a target sorting plan when the sorting efficiency parameter meets a preset condition. Thus, a sorting efficiency parameter of a sorting plan is determined by means of a digital twin, and the sorting plan is updated and iterated according to the sorting efficiency parameter, solving the problem of it not being possible to construct a data model to solve an optimal solution due to the fact that there is no objective function, optimizing the sorting plan, and improving the sorting efficiency of a sorting device.

Description

Sorting plan optimization method, device, electronic device and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to the Chinese patent application filed with the China Patent Office on June 21, 2023, with application number 202310743258X and invention name “Optimization method, device, electronic device and storage medium for sorting plan”, the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present application relates to the field of logistics technology, and in particular to a method, device, electronic device and storage medium for optimizing a sorting plan. Background Art

[0004] In the logistics field, sorting equipment deployed in transfer stations is used to sort logistics parts, that is, to classify and package logistics parts from different delivery areas for subsequent transportation. Before sorting logistics parts through sorting equipment, it is necessary to develop a sorting plan for the sorting equipment. This means assigning delivery directions to the grids at various locations on the sorting equipment, where a delivery direction is used to indicate a destination area for receiving items. The sorting plan corresponding to the sorting equipment directly affects the sorting efficiency of the sorting equipment. Therefore, how to optimize the sorting plan to improve the sorting efficiency of the sorting equipment is a technical problem that needs to be solved urgently in the relevant technology.

[0005] However, due to the complex logistics scenarios, diverse distribution of express parcels, the inability to obtain labor efficiency data, and the lack of a standard objective function to evaluate the quality of sorting plans, it is difficult to obtain the optimal solution for the sorting plan using traditional optimization methods, thereby achieving optimization of the sorting plan.

[0006] Summary of the Invention

[0007] According to various embodiments of the present application, a method, device, electronic device, and storage medium for optimizing a sorting plan are provided.

[0008] In order to achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows:

[0009] In a first aspect, an embodiment of the present application provides a method for optimizing a sorting plan, the method comprising:

[0010] Obtaining sorting efficiency parameters of the initial sorting plan;

[0011] Adjusting the initial sorting plan according to the sorting efficiency parameter of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan;

[0012] Performing sorting simulation on the intermediate sorting plan based on the digital twin to obtain sorting efficiency parameters of the intermediate sorting plan;

[0013] When the sorting efficiency parameters meet the preset conditions, the target sorting plan is obtained.

[0014] In a second aspect, an embodiment of the present application provides a device for optimizing a sorting plan, the device comprising:

[0015] An efficiency parameter acquisition module is used to obtain the sorting efficiency parameters of the initial sorting plan;

[0016] A sorting plan adjustment module is used to adjust the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan;

[0017] an efficiency parameter determination module, configured to perform a sorting simulation on the intermediate sorting plan based on the digital twin to obtain a sorting efficiency parameter of the intermediate sorting plan;

[0018] The sorting plan determination module is used to obtain a target sorting plan when the sorting efficiency parameters meet preset conditions.

[0019] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor; a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the operations of the above-mentioned method are implemented.

[0020] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the operations of the above-mentioned method when executed by a processor.

[0021] The above-mentioned sorting plan optimization method, device, electronic device, and storage medium obtain the sorting efficiency parameters of the initial sorting plan, then adjust the initial sorting plan based on the sorting efficiency parameters of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan. The intermediate sorting plan is then sorted and simulated using a digital twin to obtain the sorting efficiency parameters of the intermediate logistics plan. This process is repeated until the target sorting plan is obtained when the sorting efficiency parameters meet preset conditions. In this way, the sorting efficiency parameters of the sorting plan are determined through the digital twin, and the sorting plan is updated and iterated based on the sorting efficiency parameters. This solves the problem of having no objective function and being unable to construct a data model to find the optimal solution, realizes the optimization of the sorting plan, and can improve the sorting efficiency of the sorting equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0023] FIG1 is a schematic diagram of an application scenario of the present application according to an embodiment of the present application.

[0024] FIG2 is a flowchart of a method for optimizing a sorting plan according to an embodiment of the present application.

[0025] FIG3 is a second flowchart of a method for optimizing a sorting plan according to an embodiment of the present application.

[0026] FIG4 is a third flowchart of a method for optimizing a sorting plan according to an embodiment of the present application.

[0027] FIG5 is a block diagram of a device for optimizing a sorting plan according to an embodiment of the present application.

[0028] FIG6 shows a schematic structural diagram of an electronic device suitable for implementing the embodiments of the present application. DETAILED DESCRIPTION

[0029] The example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete, and the concepts of the example embodiments will be fully conveyed to those skilled in the art. It should be noted that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. As described in the background art, in the field of logistics, the sorting equipment deployed in the transfer yard is used to sort logistics parts, that is, to classify and pack logistics parts from different delivery areas for subsequent transportation. Before the logistics parts are sorted by the sorting equipment, a sorting plan needs to be formulated for the sorting equipment, that is, the delivery flow direction is allocated to the grids at each position on the sorting equipment, wherein one delivery flow direction is used to indicate a destination area for receiving the goods. The sorting plan corresponding to a sorting device directly affects its efficiency. Therefore, optimizing the sorting plan to improve efficiency is a pressing technical challenge in related technologies. However, due to the complexity of logistics scenarios, the diverse distribution of express shipments, the lack of access to labor efficiency data, and the lack of a standard objective function to evaluate the quality of sorting plans, traditional optimization methods have been difficult to optimize.

[0030] Based on this, the present application provides a method, device, electronic device and storage medium for optimizing a sorting plan. The sorting plan is simulated by digital twins to obtain the sorting efficiency parameters of the sorting plan. According to the sorting efficiency parameters, the sorting plan is updated and iterated, which solves the problem of having no objective function and being unable to construct a data model to find the optimal solution. The sorting plan is optimized, and the sorting efficiency of the sorting equipment can be improved.

[0031] FIG1 is a schematic diagram illustrating an application scenario of the present application according to an embodiment of the present application. As shown in FIG1 , the application scenario includes an electronic device 110, a sorting device 120, and a sorting database 130. The sorting device 120 is communicatively connected to the electronic device 110 via a wired or wireless network. The sorting database 130 can be deployed on the electronic device 110 or on a device other than the electronic device 110. The electronic device 110 can be a server (e.g., a physical server, a cloud server, etc.) or other device with certain computing capabilities. The sorting database 130 can be used to store historical sorting data for each sorting device. In other words, sorting-related data generated by the sorting device 120 during historical sorting shifts (e.g., historical sorting plans, historical supply data, and historical sorting result data) is stored in the sorting database 130. Furthermore, the sorting database 130 can also store an initial sorting plan to be optimized and the sorting efficiency parameters of the initial sorting plan.

[0032] The electronic device 110 can optimize the initial sorting plan to be optimized to obtain a target sorting plan. The specific optimization process includes: obtaining the sorting efficiency parameters of the initial sorting plan, adjusting the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan, obtaining an intermediate sorting plan corresponding to the initial sorting plan, performing sorting simulation on the intermediate sorting plan based on the digital twin, obtaining the sorting efficiency parameters of the intermediate sorting plan, and obtaining the target sorting plan when the sorting efficiency parameters meet the preset conditions. The implementation details of each of the above operations are described below. After determining the target sorting plan for the sorting device 120, the electronic device 110 can send the target sorting plan to the sorting device 120 so that the sorting device sets the delivery flow direction of the grid at each position according to the target sorting plan.

[0033] The following is a detailed description of the implementation details of the technical solution of the embodiment of the present application:

[0034] FIG2 is a flowchart of a method for optimizing a sorting plan according to an embodiment of the present application. The method can be executed by an electronic device with processing capabilities, which can be a server. Referring to FIG2 , the method includes at least operations 210 to 240, which are described in detail as follows:

[0035] Operation 210 , obtaining sorting efficiency parameters of the initial sorting plan;

[0036] In this application, the initial sorting plan is the sorting plan to be optimized. In some embodiments, the initial sorting plan may be developed by the sorting staff based on their work experience. In this application, the sorting plan is a plan developed to improve the efficiency of the sorting equipment. In this application, the sorting plan may include the location of the slots assigned to each delivery flow direction and the number of slots assigned to each delivery flow direction. In practice, the initial sorting plan may have unreasonable aspects. For example, if the delivery flow directions corresponding to the slots on the sorting equipment are assigned according to the initial sorting plan, there may be a large difference in the number of items dropped between some different slots during the sorting process. This will result in the slots not being fully utilized, and thus causing the sorting efficiency of the sorting equipment to be low according to the initial sorting plan. Therefore, it is necessary to optimize the initial sorting plan. In this application, the sorting plan can be optimized based on a sorting efficiency parameter. The sorting efficiency parameter can be the production capacity corresponding to the sorting plan, that is, the production capacity of the sorting equipment when the sorting plan is applied to the sorting equipment. The sorting efficiency parameters may be, but are not limited to, one or more of the sorting time, the number of express parcels sorted per unit time, and the amount of bags dropped in half a circle within a preset time. The parameter of the amount of bags dropped in half a circle within a preset time is applicable to ring sorting equipment, which refers to the number of logistics pieces that fall from the grid within a preset time when the transmission distance on the ring sorting equipment does not exceed half a circle. In the present application, when the initial sorting plan is formulated by the sorting staff based on their own work experience, the sorting efficiency parameters of the initial sorting plan can be the production capacity of the actual site (such as the sorting equipment in the transfer yard) to implement the initial sorting plan, or it can be the production capacity set by the sorting staff for the initial sorting plan.

[0037] Operation 220 : adjusting the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan.

[0038] In the present application, during the optimization process of the sorting plan, after obtaining the sorting efficiency parameters of the sorting plan, it is possible to detect whether the sorting efficiency parameters of the sorting plan meet pre-set preset conditions. If the sorting efficiency parameters of the sorting plan do not meet the preset conditions, the sorting plan needs to be adjusted. Therefore, after obtaining the sorting efficiency parameters of the initial sorting plan, it is possible to detect whether the sorting efficiency parameters of the initial sorting plan meet the preset conditions. If they do not meet the preset conditions, the initial sorting plan is adjusted. It is understandable that since the initial sorting plan is the sorting plan to be optimized, in order to improve efficiency, it is not necessary to detect whether the sorting efficiency parameters of the initial sorting plan meet the preset conditions. After obtaining the sorting efficiency parameters of the initial sorting plan, the initial sorting plan can be directly adjusted. Optionally, in the present application, adjusting the initial sorting plan can be adjusting the number of slots allocated to each delivery flow in the initial sorting plan. Optionally, in the present application, when adjusting the number of slots in the bins assigned to each delivery flow in the initial sorting plan, the number of slots in the bins assigned to each delivery flow in the initial sorting plan can be adjusted according to the set adjustment amount. For example, during each adjustment, the number of slots in the bins assigned to each delivery flow can be increased by A, or decreased by A. Optionally, in the present application, when adjusting the initial sorting plan, the bin positions of the bins assigned to each delivery flow in the initial sorting plan can be adjusted. Optionally, in the present application, when adjusting the bin positions of the bins assigned to each delivery flow in the initial sorting plan, the bin positions of the bins assigned to each delivery flow in the initial sorting plan can be adjusted randomly, or the bin positions of the bins assigned to each delivery flow can be adjusted based on the supply area corresponding to each delivery flow. For example, for each delivery direction, if the delivery area for that delivery direction is Area A or Area B, the slot position of the slot assigned to that delivery direction can be adjusted to Area A or Area B. In this application, after adjusting the initial sorting plan, an intermediate sorting plan corresponding to the initial sorting plan can be obtained. It can be understood that the intermediate sorting plan is a sorting plan that is in the process of being optimized but has not yet been fully optimized.

[0039] Operation 230 : performing a sorting simulation on the intermediate sorting plan based on the digital twin to obtain sorting efficiency parameters of the intermediate sorting plan.

[0040] Among them, after obtaining the intermediate sorting plan, the intermediate sorting plan can be sorted and simulated through the digital twin, and the sorting efficiency parameters of the intermediate sorting plan can be output. Digital twin, also known as digital twin (Digital Twin), is a digital mapping of physical objects. In the present application, the digital twin is a digital mapping of the sorting equipment, and the digital twin is a dynamic simulation of the sorting equipment. Therefore, the sorting efficiency parameters of the sorting plan can be accurately reflected through the digital twin. In the present application, the sorting efficiency parameters of the sorting plan are determined by the digital twin, and the sorting efficiency parameters of the sorting plan can be accurately obtained without implementing the sorting plan. In this way, the optimization efficiency of the sorting plan can be improved, and the accuracy of the sorting efficiency parameters can also be guaranteed.

[0041] Operation 240 : When the sorting efficiency parameter satisfies a preset condition, a target sorting plan is obtained.

[0042] Among them, after obtaining the sorting efficiency parameters of the intermediate sorting plan through the digital twin, it is possible to detect whether the sorting efficiency parameters of the intermediate sorting plan meet the preset conditions. If the sorting efficiency parameters of the intermediate sorting plan do not meet the preset conditions, then continue to adjust the intermediate sorting plan, that is, continue to adjust the number of slots allocated to each delivery flow in the intermediate sorting plan to obtain the adjusted intermediate sorting plan. After obtaining the adjusted intermediate sorting plan, the digital twin can be used again to perform sorting simulation on the adjusted intermediate sorting plan to obtain the sorting efficiency parameters of the adjusted intermediate sorting plan. Then, it is detected whether the sorting efficiency parameters of the adjusted intermediate sorting plan meet the preset conditions, and it is iterated until the sorting efficiency parameters of the intermediate sorting plan are adjusted to meet the preset conditions. The intermediate sorting plan whose sorting efficiency parameters meet the preset conditions is determined as the target sorting plan. In this application, the preset condition can be that the sorting efficiency parameter reaches convergence, or that the sorting efficiency parameter is greater than the set sorting efficiency threshold, and there is no specific limitation. It can be understood that in this application, the target sorting plan represents the optimized sorting plan. After obtaining the target sorting plan, the target sorting plan can be sent to the sorting equipment, and the sorting equipment will allocate the delivery flow direction corresponding to each grid on the sorting equipment according to the target sorting plan, thereby realizing the sorting of express parcels. The optimization method of the sorting plan provided in this application, after obtaining the sorting efficiency parameters of the initial sorting plan, adjusts the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan, obtains the intermediate sorting plan corresponding to the initial sorting plan, and performs sorting simulation on the intermediate sorting plan through the digital twin to obtain the sorting efficiency parameters of the intermediate logistics plan. This is repeated, and when the sorting efficiency parameters meet the preset conditions, the target sorting plan is obtained. In this way, the sorting efficiency parameters of the sorting plan are determined by the digital twin, and the sorting plan is updated and iterated according to the sorting efficiency parameters, which solves the problem of no objective function and the inability to construct a data model to find the optimal solution, realizes the optimization of the sorting plan, and can improve the sorting efficiency of the sorting equipment.

[0043] In view of the fact that the sorting plan directly affects the sorting efficiency of the sorting equipment in practical applications, in order to optimize the sorting plan faster and better, in this application, the initial sorting plan is adjusted according to the sorting efficiency parameters of the initial sorting plan. The operation of obtaining the intermediate sorting plan corresponding to the initial sorting plan may also include:

[0044] (1) According to the sorting efficiency parameters corresponding to the initial sorting plan, the sorting hyperparameters are adjusted to obtain the adjusted sorting hyperparameters. (2) According to the adjusted sorting hyperparameters, the initial sorting plan is adjusted to obtain the intermediate sorting plan. In this application, the sorting hyperparameters refer to parameters used to reflect the sorting distribution situation on the sorting equipment. The sorting hyperparameters include at least one of the maximum capacity of the grid, the minimum capacity of the grid, the ratio of the infeeds of different infeeds, and the average number of scans.

[0045] The maximum slot capacity refers to the maximum number of parcels that can be dropped from a slot; correspondingly, the minimum slot capacity refers to the minimum number of parcels that can be dropped from a slot. For the slots in a sorting device, if the slot capacities of different slots differ significantly—for example, if slot A has a larger slot capacity (i.e., more parcels can be dropped from this slot) and slot B has a smaller slot capacity (i.e., fewer parcels can be dropped from this slot), this indicates that the number of slots allocated to the delivery flow corresponding to slot A and slot B is not appropriate, resulting in significant differences in the number of parcels dropped from different slots. Consequently, when a parcel reaches slot A, there's a high probability that the slot will be locked (the slot is locked after a bulk bag is full and then opened by the bagging staff after replacing the bulk bag). Consequently, the parcel will need to continue on the conveyor belt, awaiting the next slot corresponding to the delivery flow. There are usually multiple infeeds on the sorting equipment. Express parcels enter the conveyor belt of the sorting equipment from the infeeds, and then flow to the grid corresponding to the delivery direction to which the logistics parcel belongs and fall. The supply ratio of different infeeds refers to the proportion of parcels from different infeeds. Furthermore, the supply ratio of different infeeds can be counted for each delivery direction. For example, for delivery direction K, Q1 parcels are fed from infeed P1, and Q2 parcels are fed from infeed P2. Then, the supply ratio of infeed P1 for delivery direction K is Q1 / (Q1+Q2), and the supply ratio of infeed P2 is Q2 / (Q1+Q2). The number of scans for a parcel refers to the number of times the parcel passes through the six-sided scanning device before falling into the bag. For example, if the number of scans for a parcel is 2, it means that the parcel has passed through the six-sided scanning device twice, but no parcel fell into the bag. This indicates that the slot corresponding to the delivery flow direction to which the parcel belongs is locked (that is, the slot is full at this time and is waiting for the bagger to replace the bag). If the average number of scans for parcels corresponding to a delivery flow direction is high, it indicates that the number of slots allocated to the delivery flow direction is relatively small. In a specific embodiment, the average number of scans can be the average of the scans for all parcels in a sorting shift, or it can be counted by delivery flow direction, that is, the average number of scans for all parcels corresponding to each delivery flow direction in a sorting shift is counted.

[0046] Optionally, in the optimization of this sorting plan, the initial value of the sorting hyperparameter can be set by the staff. This situation is usually used for the formulation of the sorting plan of a newly built transfer station. In the optimization of this sorting plan, the initial value of the sorting hyperparameter can also be the value of the final sorting hyperparameter determined during the previous optimization. This situation is usually used for the optimization of the sorting plan of the transfer station in use. Optionally, in the present application, when adjusting the sorting hyperparameter according to the sorting efficiency parameter corresponding to the initial sorting plan, the change ratio of the sorting efficiency parameter corresponding to the initial sorting plan relative to the sorting efficiency parameter of the previous sorting plan can be determined first, and then the adjustment value of the sorting hyperparameter is determined based on the change ratio and the preset ratio adjustment value relationship data, and the numerical value of the sorting hyperparameter is adjusted according to the adjustment value of the sorting hyperparameter. Among them, the ratio adjustment value relationship data is used to indicate the mapping relationship data between the change ratio of the sorting efficiency parameter and the adjustment value. For example, the ratio adjustment value relationship data includes a mapping relationship between the A ratio and the a adjustment value, and a mapping relationship between the B ratio and the b adjustment value. Assuming that the ratio of change in the sorting efficiency parameter corresponding to the initial sorting plan relative to the sorting efficiency parameter of the previous sorting plan is A, the sorting hyperparameter adjustment value can be obtained as a, and the sorting hyperparameter is then adjusted based on the adjustment value a. It is understood that when the sorting hyperparameter includes multiple parameters, the sorting hyperparameter adjustment value includes the adjustment value of each parameter. Optionally, when the sorting hyperparameter includes multiple parameters, when adjusting the value of the sorting hyperparameter, only one parameter can be adjusted at a time, or multiple parameters can be adjusted simultaneously at a time. Optionally, in some embodiments of the present application, the value of the sorting hyperparameter can also be adjusted based on a set adjustment step size. Specifically, if the optimal sorting plan needs to be found quickly, the adjustment step size can be set larger. If the most accurate optimal sorting plan needs to be found, the adjustment step size can be set smaller. There are no specific limitations and the adjustment step size can be set based on actual needs. After adjusting the values ​​of the sorting hyperparameters, adjusted sorting hyperparameters can be obtained. After obtaining the adjusted sorting hyperparameters, the initial sorting plan can be adjusted according to the adjusted sorting hyperparameters to obtain an intermediate sorting plan.

[0047] In the present application, when the initial sorting plan is adjusted according to the adjusted sorting hyperparameters, the number of grids and the position of grids corresponding to the delivery directions in the initial sorting plan may be adjusted. Therefore, in the present application, the operation of adjusting the initial sorting plan according to the adjusted sorting hyperparameters to obtain the intermediate sorting plan may also include: (a1) adjusting the number of grids and the grid area corresponding to the delivery directions in the initial sorting plan according to the adjusted sorting hyperparameters to obtain the target number of grids and the target grid area corresponding to each delivery direction in the initial sorting plan. (a2) obtaining the intermediate sorting plan based on the target number of grids and the target grid area corresponding to each delivery direction in the initial sorting plan. The initial sorting plan includes the position of the grids assigned to each delivery direction and the number of grids assigned to each delivery direction. The position of each grid belongs to a grid area, and the grid areas to which the positions of each grid belong may be the same or different. For example, there are slots A, B, and C, where slot A is located in the slot area of ​​the A infeed table, slot B is located in the slot area of ​​the B infeed table, and slot C is located in the slot area of ​​the A infeed table.

[0048] Optionally, the number of slots and slot areas corresponding to the delivery flow direction in the initial sorting plan are adjusted based on the adjusted sorting hyperparameters. The historical sorting data of the sorting equipment corresponding to the initial sorting plan can be obtained first. The historical sorting data includes sorting information of each express parcel, including but not limited to the corresponding delivery flow direction, the corresponding delivery table, the number of scans, etc.

[0049] After obtaining historical sorting data, the historical delivery volume corresponding to each delivery direction, the historical delivery ratio of different induction stations, and the historical average number of scans for express parcels can be determined based on the historical sorting data. Then, based on the adjusted sorting hyperparameters, the historical delivery volume corresponding to each delivery direction, the historical delivery ratio of different induction stations, and the historical average number of scans for express parcels, the number of slots and slot areas corresponding to each delivery direction in the initial sorting plan are adjusted to obtain the target number of slots and target slot areas corresponding to each delivery direction in the initial sorting plan. When adjusting the number of slots corresponding to each delivery direction in the initial sorting plan, the historical delivery volume corresponding to each delivery direction can be compared with the minimum slot capacity in the sorting hyperparameters for each delivery direction. If the historical delivery volume corresponding to the delivery direction is less than the minimum slot capacity in the sorting hyperparameters, it indicates that the delivery volume corresponding to the delivery direction is small. Considering practical applications, each delivery direction is assigned at least one slot to sort its parcels. Therefore, for each delivery direction, if the historical delivery volume for that direction is less than the minimum slot capacity specified in the sorting hyperparameters, the number of slots associated with that direction can be adjusted to 1, i.e., the target number of slots for that direction is 1.

[0050] For each delivery direction, if the historical delivery volume corresponding to the delivery direction is not less than the minimum slot capacity in the sorting hyperparameters, the historical delivery volume corresponding to the delivery direction is compared with the maximum slot capacity in the sorting hyperparameters. If the historical delivery volume corresponding to the delivery direction is not greater than the maximum slot capacity in the sorting hyperparameters, the number of slots assigned to the delivery direction can be reduced according to the set adjustment amount to obtain the target number of slots corresponding to the delivery direction. It can be understood that if the historical delivery volume corresponding to the delivery direction is not greater than the maximum slot capacity in the sorting hyperparameters, but the number of slots corresponding to the delivery direction is 1, there is no need to reduce the number of slots corresponding to the delivery direction, that is, the target number of slots corresponding to the delivery direction is 1. If the historical delivery volume corresponding to the delivery direction is greater than the maximum slot capacity in the sorting hyperparameters, the number of slots assigned to the delivery direction can be increased according to the set adjustment amount to obtain the target number of slots corresponding to the delivery direction. Considering the different environments and parcel handling efficiencies of different slots in practical applications, different slots handle different parcels. For example, if a slot without printing equipment or staff is locked, it will be unable to process parcels for a long time, resulting in a low volume of parcels. In this case, additional slots may be necessary. However, if a slot with printing equipment and staff is locked, the lock will be quickly resolved, resulting in a smaller impact on parcel volume. In this case, additional slots may not be necessary. When a slot is locked for an extended period, the number of scans required for parcels landing in that slot increases. Therefore, to ensure accurate adjustment of the number of slots, in this application, for each delivery direction, when the historical delivery volume corresponding to that delivery direction exceeds the maximum slot capacity in the sorting hyperparameters, the historical average number of scans corresponding to that delivery direction may be compared with the average number of scans in the sorting hyperparameters. If the historical delivery volume for this delivery direction exceeds the maximum slot capacity in the sorting hyperparameters, and the historical average number of scans for this delivery direction exceeds the average number of scans in the sorting hyperparameters, the number of slots assigned to this delivery direction will be increased by the set adjustment amount to obtain the target number of slots for this delivery direction. If the historical delivery volume for this delivery direction exceeds the maximum slot capacity in the sorting hyperparameters, but the historical average number of scans for this delivery direction does not exceed the average number of scans in the sorting hyperparameters, then there is no need to adjust the number of slots for this delivery direction, and the number of slots for this delivery direction in the initial sorting plan will be determined as the target number of slots for this delivery direction.

[0051] When adjusting the slot areas corresponding to the delivery directions in the initial sorting plan, for each delivery direction, the historical induction ratios of each induction station corresponding to that delivery direction can be compared with the induction ratios of each induction station in the sorting hyperparameters. A target induction station whose historical induction ratio is greater than the induction ratio of the corresponding induction station in the sorting hyperparameters is determined. Once the target induction station is determined, the slot area of ​​the target induction station can be determined as the target slot area for that delivery direction. For example, for inductions A and B, assuming the induction ratio of induction A in the sorting hyperparameters is x1 and the ratio of induction B is x2, and the historical induction ratio of a delivery direction at induction A is y1 and the historical ratio at induction B is y2, if y1 is greater than x1 and y2 is less than x2, induction A is determined as the target induction station, and the slot area of ​​induction A becomes the target slot area for that delivery direction. It can be understood that for each delivery direction in the initial sorting plan, after obtaining the target number of slots and target slot area corresponding to each delivery direction, a target number of slots can be selected from the target slot area corresponding to each delivery direction as the target slot for that delivery direction. After obtaining the target slots for each delivery direction, the intermediate sorting plan can be derived based on the target slots for each delivery direction.

[0052] In order to improve the accuracy of the slots corresponding to each delivery flow direction, in this application, the target slots for each delivery flow direction can also be determined based on the flow direction priority and the slot priority. Therefore, based on the target slot number and target slot area corresponding to each delivery flow direction in the initial sorting plan, the operation of obtaining the intermediate sorting plan can also include: (b1) obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting equipment corresponding to the initial sorting plan. (b2) matching the delivery flow direction with the slots based on the target slot number and target slot area corresponding to each delivery flow direction in the initial sorting plan, the flow direction priority corresponding to each delivery flow direction in the initial sorting plan, and the slot priority corresponding to each slot in the sorting equipment corresponding to the initial sorting plan to obtain the intermediate sorting plan.

[0053] In some embodiments, before operation b1, the method further includes: determining the grid priority corresponding to each grid in the sorting device based on at least one of the distance between the grid and the printing device, the supply table corresponding to the grid, the distance between the grid and the turning position of the conveyor belt, and the distribution density of the packaging operation objects in the grid area where the grid is located.

[0054] After packing, the packing personnel need to use the printing device to print the logistics certificate corresponding to the corresponding bag. It is understandable that if the distance between the grid opening and the printing device is smaller, the packing personnel will have to move a shorter distance, and the packing personnel will not need to spend more energy and time to print the logistics certificate. Therefore, it can be set that the grid opening with a larger distance from the printing device has a higher priority; conversely, the grid opening with a smaller distance from the printing device has a lower priority. For express parcels, the closer the grid opening is to the turning point of the conveyor belt, the more likely the parcel will float, causing the parcel to fall from other grid openings. Therefore, it can be set that the grid opening with a smaller distance from the turning point of the conveyor belt has a lower priority, and the grid opening with a larger distance from the turning point of the conveyor belt has a higher priority. The distribution density of packing operation objects within the grid area where a slot is located reflects the number of packing operation objects assigned to that area. Since the number of slots in a grid area is fixed, the number of slots a single packing operation object (i.e., packing personnel) is responsible for can be determined based on the distribution density of packing operation objects within the grid area where the grid is located. For a slot, if it is located in a grid area with a high density of packing operation objects, the slot has a higher priority; conversely, if it is located in a grid area with a low density of packing operation objects, the slot has a lower priority. Induction tables are used to supply items to the slots within a given area. Different induction tables are responsible for different induction areas. It can be set so that the more slots a slot in an induction table's grid area has, the higher the priority of the slot in that area.

[0055] In some embodiments, if the slot priority corresponding to each slot in the sorting device is determined based on the distance between the slot and the printing device, the infeed corresponding to the slot, the distance between the slot and the turning position of the conveyor belt, and the distribution density of the objects for the packaging operation in the slot area where the slot is located, the operation specifically includes: determining a first priority score corresponding to each slot based on the distance between the slot and the printing device; determining a second priority score corresponding to each slot based on the infeed corresponding to the slot; determining a third priority score corresponding to each slot based on the distance between the slot and the turning position of the conveyor belt; determining a fourth priority score corresponding to each slot based on the distribution density of the objects for the packaging operation in the slot area where the slot is located; and determining a total priority score corresponding to each slot by performing weighted calculation based on the first priority score, the second priority score, the third priority score, and the fourth priority score corresponding to each slot, wherein the total priority score corresponding to the slot is positively correlated with the slot priority corresponding to the slot, that is, the higher the total priority score of the slot, the higher the slot priority of the slot. In a specific embodiment, the weighting coefficients corresponding to the first priority score, the second priority score, the third priority score, and the fourth priority score can be set according to actual needs and are not specifically limited here.

[0056] In some embodiments, before operation b1, the method further includes: determining the flow direction priority corresponding to each delivery flow direction based on at least one of the province type corresponding to each delivery flow direction, the timeliness type corresponding to each delivery flow direction, and the flow type corresponding to each delivery flow direction. The province types corresponding to the delivery flow directions include within the province and outside the province. Generally, the grids corresponding to the delivery flow directions within the province are deployed together. For the delivery flow directions outside the province, the delivery flows of adjacent provinces are placed adjacent to each other. This avoids the long distance required for re-delivery after incorrect sorting of express parcels due to floating parcels. The priority of the delivery flow direction corresponding to the province can be set to be higher than the priority of the delivery flow direction outside the province. The timeliness type corresponding to the delivery flow direction is used to indicate the timeliness of the delivery flow direction. It can be set that the delivery flow direction with a higher timeliness requirement indicated by the corresponding timeliness type has a higher priority, and the delivery flow direction with a lower timeliness requirement has a lower priority.

[0057] The traffic type corresponding to the delivery flow direction indicates the relative size of the number of express parcels corresponding to the delivery flow direction. It can be set that the delivery flow direction with a larger number of express parcels indicated by the corresponding flow direction type has a higher priority, that is, the priority of the delivery flow direction with a large flow direction is higher than the priority of the delivery flow direction with a small flow direction.

[0058] In some embodiments, if the flow priority corresponding to each delivery direction is determined based on the province type corresponding to each delivery direction, the timeliness type corresponding to each delivery direction, and the traffic type corresponding to each delivery direction, it can be determined specifically according to the following operations: determine the first flow priority score corresponding to each delivery direction according to the province type corresponding to each delivery direction; determine the second flow priority score corresponding to each delivery direction according to the timeliness type corresponding to each delivery direction; determine the third flow priority score corresponding to each delivery direction according to the traffic type corresponding to each delivery direction; perform weighted calculation based on the first flow priority score corresponding to each delivery direction, the corresponding second flow priority score and the corresponding third flow priority score corresponding to each delivery direction, wherein the total flow priority score corresponding to the delivery direction is positively correlated with the flow priority corresponding to the delivery direction, that is, the higher the total flow priority score corresponding to the delivery direction, the higher the flow priority corresponding to the delivery direction. In a specific embodiment, the weighting coefficients corresponding to the first flow direction priority score, the second flow direction priority score, and the third flow direction priority score can be set according to actual needs and are not specifically limited here. After obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting equipment corresponding to the initial sorting plan, the delivery flow directions can be matched with the slots based on the target slot number and target slot area corresponding to each delivery flow direction in the initial sorting plan, the flow direction priority corresponding to each delivery flow direction in the initial sorting plan, and the slot priority corresponding to each slot in the sorting equipment corresponding to the initial sorting plan to obtain an intermediate sorting plan.

[0059] In some embodiments, as shown in FIG3 , the corresponding slots of each delivery direction can be determined according to the following operations 310 to 340 to obtain an intermediate sorting plan. Specifically:

[0060] Operation 310 : Determine the target slot priority corresponding to the flow direction priority corresponding to each delivery flow direction according to the correspondence between the slot priority and the flow direction priority.

[0061] Operation 320 : For each delivery flow direction, determine the slot pre-assigned to the delivery flow direction according to the target slot priority corresponding to the delivery flow direction.

[0062] Operation 330 : Obtain the target slot corresponding to the delivery direction from the slots pre-assigned to the delivery direction according to the target slot area corresponding to the delivery direction and the number of target slots corresponding to the delivery direction.

[0063] Operation 340 : Obtain an intermediate sorting plan based on the target slots corresponding to the delivery directions.

[0064] The correspondence between slot priorities and flow direction priorities can be set according to actual needs. For example, if the number of slot priority levels is the same as the number of flow direction priority levels, slot priorities of the same level can be set to correspond to flow direction priorities. Currently, this is not limited to this in practice. In a specific embodiment, a flow direction priority can correspond to one slot priority or multiple slot priorities. It is understood that the slots assigned to different delivery flow directions in a sorting plan are not repeated, that is, during the allocation process, a slot on the sorting device corresponds to at most one delivery flow direction. In operation 320, for each delivery flow direction, the slot priority of each slot can be matched with the target slot priority corresponding to the delivery flow direction, and the slot with the target slot priority can be selected. The selected slot with the target slot priority is determined as the pre-assigned slot for the delivery flow direction. For each delivery direction, after obtaining the pre-assigned grid openings for the delivery direction, you can select the target grid opening areas and the target grid opening number corresponding to the delivery direction from the pre-assigned grid openings for the delivery direction, and use the selected grid openings as the target grid openings corresponding to the delivery direction.

[0065] For example, for a certain transfer yard, there are grid area L1, grid area L2, and grid area L3, among which grid area L1 includes grid K1, grid K2, and grid K3, grid area L2 includes grid K4 and grid K5, and grid area L3 includes grid K6. The grid priority of grids K1 and K4 is N1, the grid priority of grids K2, K5, and K6 is N2, and the grid priority of grid K3 is N3. For the delivery direction M, assuming that the target grid priority corresponding to the delivery direction M is N1, the number of target grids is 1, and the corresponding target grid area is L1, then K1 can be determined as the target grid corresponding to the delivery direction.

[0066] In some embodiments, in order to obtain more suitable and accurate grid slots for each delivery flow direction, in this application, grid slot allocation constraints can also be set. According to the grid slot allocation constraints, the target grid slot area corresponding to the delivery flow direction, and the target grid slot number corresponding to the delivery flow direction, the target grid slot corresponding to the delivery flow direction is obtained from the grid slots pre-allocated to the delivery flow direction. Among them, the grid slot allocation constraint can be that for the same delivery flow direction, if multiple grid slots need to be allocated, then the multiple grid slots need to be allocated to each target grid slot area corresponding to the delivery flow direction, rather than to one target grid slot area; for example, if the L1 target grid slot area includes 50 grid slots and the L2 target grid slot area includes 70 grid slots, if a delivery flow direction needs to be allocated two grid slots, that is, the corresponding target grid slot number is 2, then one grid slot allocated to the delivery flow direction is located in the L1 target grid slot area and the other is located in the L2 target grid slot area. Optionally, the slot allocation constraint can also be that for the same delivery flow, if multiple slots need to be allocated to it, then according to the set slot allocation ratio, some of the multiple slots need to be allocated to the target slot areas corresponding to the delivery flow, and the remaining slots need to be allocated to other slot areas. For example, if the L1 target slot area includes 50 slots, the L2 target slot area includes 70 slots, and the L3 slot area has 60 slots, if a delivery flow needs to be allocated to 3 slots, assuming the set slot allocation ratio is target slot area: other slot areas = 2:1, then of the slots allocated to the delivery flow, 2 need to be allocated to the target slot areas, and 1 needs to be allocated to other slot areas, that is, 2 need to be allocated to the L1 target slot area and the L2 target slot area, and 1 need to be allocated to the L3 slot area. Optionally, the slot allocation constraints may also include constraints such as the number of consecutive slots for the same delivery flow direction not exceeding a quantity threshold, the slots corresponding to the corresponding delivery flow direction being a large flow direction cannot be consecutive, and the like. These constraints may be set based on actual needs and are not specifically limited here. After obtaining the target slots corresponding to each delivery flow direction, an intermediate sorting plan may be obtained based on the target slots corresponding to each delivery flow direction. It is understandable that in the present application, after obtaining the intermediate sorting plan, a digital twin may be used to perform sorting simulation on the intermediate sorting plan to obtain the sorting efficiency parameters of the intermediate sorting plan.

[0067] As described above, the digital twin is a digital mapping of the sorting equipment. The digital twin is a dynamic simulation of the sorting equipment. The digital twin can simulate the sorting equipment to perform sorting simulation. Specifically, the sorting simulation can be performed through the following operations:

[0068] According to the intermediate sorting plan, determine the target delivery direction corresponding to each grid on the sorting equipment.

[0069] Based on the digital twin, the reference supply data is sorted and simulated according to the target delivery flow direction corresponding to each grid on the sorting equipment to obtain the sorting efficiency parameters corresponding to the intermediate sorting plan.

[0070] Among them, when using the digital twin to simulate the sorting of the intermediate sorting plan, the target delivery flow direction corresponding to each grid on the sorting equipment can be allocated according to the intermediate sorting plan. Then, the digital twin simulates the sorting of the reference supply data according to the target delivery flow direction corresponding to each grid on the sorting equipment. In this way, the sorting efficiency parameters corresponding to the intermediate sorting plan can be obtained.

[0071] The reference parcel data may be the parcel data of the sorting shift corresponding to the sorting plan, and the parcel data may include at least the parcel information of the parcel to be sorted, such as the parcel receiving address, the object type of the parcel, the weight of the parcel, the volume of the parcel, etc.

[0072] The sorting efficiency parameters corresponding to a sorting plan can include, but are not limited to, sorting time, the number of parcels sorted per unit time, and the amount of parcels dropped during a half-turn delivery within a preset time period. These sorting efficiency parameters can reflect the sorting efficiency corresponding to the sorting plan. If the sorting efficiency parameter is sorting time, the shorter the sorting time, the higher the sorting efficiency. If the sorting efficiency parameter is the number of parcels sorted per unit time, the greater the number of parcels sorted per unit time, the higher the sorting efficiency. If the sorting efficiency parameter is the amount of parcels dropped during a half-turn delivery within a preset time period, the greater the amount of parcels dropped during a half-turn delivery within the preset time period, the higher the sorting efficiency.

[0073] In some embodiments, if the sorting efficiency parameters include multiple factors such as the sorting time, the number of parcels sorted per unit time, and the number of parcels dropped in half a circle within a preset time, the sorting efficiency score of the sorting plan corresponding to each type of sorting efficiency parameter can be determined based on the sorting efficiency parameters of each type corresponding to the sorting plan. The sorting efficiency scores of the sorting plan under multiple types of sorting efficiency parameters are weighted and calculated to obtain a total sorting efficiency score corresponding to the sorting plan. The total sorting efficiency score is then used as the final sorting efficiency parameter.

[0074] In this embodiment, after obtaining the sorting efficiency parameters of the intermediate sorting plan, the sorting efficiency parameters of the intermediate sorting plan can be tested to determine whether the sorting efficiency parameters of the intermediate sorting plan meet the preset conditions, thereby obtaining a target sorting plan whose sorting efficiency parameters meet the preset conditions. Optionally, this can be achieved by the following operations:

[0075] If the sorting efficiency parameters of the intermediate sorting plan do not meet the preset conditions, the intermediate sorting plan is adjusted based on the sorting efficiency parameters of the intermediate sorting plan to obtain a new intermediate sorting plan. A sorting simulation of the new intermediate sorting plan is performed based on the digital twin to obtain the sorting efficiency parameters of the new intermediate sorting plan. If the sorting efficiency parameters of the new intermediate sorting plan meet the preset conditions, the new intermediate sorting plan is determined as the target sorting plan. If the sorting efficiency parameters of the new intermediate sorting plan do not meet the preset conditions, the new intermediate sorting plan is adjusted based on the sorting efficiency parameters of the new intermediate sorting plan. This iteration is repeated until sorting efficiency parameters that meet the preset conditions are obtained. The sorting plan corresponding to the sorting efficiency parameters that meet the preset conditions is determined as the target sorting plan.

[0076] Among them, after obtaining the sorting efficiency parameters of the intermediate sorting plan, the sorting efficiency parameters of the intermediate sorting plan are tested. If the sorting efficiency parameters of the intermediate sorting plan still do not meet the preset conditions, the adjusted sorting hyperparameters are further adjusted according to the sorting efficiency parameters of the intermediate sorting plan to obtain new adjusted sorting hyperparameters. Then, according to the new adjusted sorting hyperparameters, the number of slots and the slot area corresponding to the delivery direction in the intermediate sorting plan are adjusted to obtain a new intermediate sorting plan. Thereafter, the new intermediate sorting plan is sorted and simulated through the digital twin to determine the sorting efficiency parameters of the new intermediate sorting plan. After obtaining the sorting efficiency parameters of the new intermediate sorting plan, it is detected whether the sorting efficiency parameters of the new intermediate sorting plan meet the preset conditions. If the preset conditions are met, the new intermediate sorting plan is determined as the target sorting plan. If the preset conditions are still not met, the sorting hyperparameters are adjusted according to the sorting efficiency parameters of the new intermediate sorting plan, that is, the new intermediate sorting plan is adjusted continuously. This is iterated until the sorting efficiency parameters that meet the preset conditions are obtained, and the intermediate sorting plan corresponding to the sorting efficiency parameters that meet the preset conditions is determined as the target sorting plan.

[0077] The process of adjusting the adjusted sorting hyperparameters and adjusting the number of slots and slot areas corresponding to the delivery directions in the intermediate sorting plan based on the newly adjusted sorting hyperparameters can be found in the above description and will not be repeated here.

[0078] In the present application, by optimizing and iterating the sorting hyperparameters, and then determining the number of grids and grid area corresponding to the delivery flow direction based on the sorting hyperparameters, the rationality of the number of grids and grid distribution corresponding to each delivery flow direction can be guaranteed, avoiding excessive differences in the flow of different grids. In addition, according to the target number of grids and target grid area corresponding to each delivery flow direction in the sorting plan, the flow priority corresponding to each delivery flow direction in the sorting plan, and the grid priority corresponding to each grid in the sorting equipment corresponding to the initial sorting plan, the delivery flow direction is matched with the grid, which can ensure that the flow corresponding to different grids in the final target sorting plan is basically the same, and can avoid the problem of low grid utilization due to excessive differences in the flow of different grids; thereby, the sorting efficiency of the sorting equipment in sorting according to the optimized target sorting plan can be improved.

[0079] In some embodiments, as shown in FIG4 , in order to ensure the accuracy of the obtained sorting efficiency parameters and the accuracy of the target sorting plan obtained, the method further includes the following operations 410 to 430 , which are described in detail as follows:

[0080] Operation 410 : constructing a digital twin corresponding to the sorting device based on the structural information of the sorting device and the action mechanism information between different components in the sorting device.

[0081] The digital twin of the sorting equipment is a three-dimensional virtual model constructed based on the physical attribute data of each component in the sorting equipment and the information about the action mechanism between different components. In some embodiments, the digital twin of the sorting equipment can be constructed according to the process shown in the following operations A1-A3, which are described in detail as follows:

[0082] Operation A1: Obtain entity attribute data of each component in the sorting equipment.

[0083] Components in the sorting equipment include six-sided scanning devices, induction tables, printing devices, sorting conveyors, and slots. Component entity attribute data refers to data reflecting the static properties of the component, such as its dimensions and physical properties (e.g., the number of slots, the width of the slots, the spacing between the slots, etc.).

[0084] Operation A2: Modeling is performed based on entity attribute data to obtain digital twin entities of each component.

[0085] The digital twin of a component is a three-dimensional virtual model of the component. In operation A2, modeling can be performed based on the component's structural information (e.g., dimensions) to obtain the component's digital twin, which can be understood as a three-dimensional model of the component.

[0086] Operation A3: Based on the action mechanism information between different components in the sorting system, the digital twin monomers corresponding to different components are associated to obtain the digital twin corresponding to the sorting equipment.

[0087] The multiple components of the sorting equipment collaborate to sort parcels. The action mechanism information between these components reflects the relationships between them, such as the relative positional relationships between different physical objects and the action relationships between different physical objects. This action mechanism information can be used to associate the actions of different digital twin entities. The resulting digital twin can reflect the action relationships between the different components of the sorting equipment. The resulting digital twin of the sorting equipment can then be used to simulate the dynamic sorting process of the sorting equipment.

[0088] Operation 420 : Performing a sorting simulation based on the historical sorting plan corresponding to the sorting equipment and the historical part supply data corresponding to the historical sorting plan through the digital twin to obtain simulated sorting result data corresponding to the historical sorting plan.

[0089] In practice, the digital twin constructed for a sorting device may not accurately replicate the sorting process of the sorting device. In this embodiment, to address this issue, the digital twin corresponding to the sorting system is optimized for fidelity based on historical sorting data collected during the actual operation of the sorting device. This allows the sorting effect of the optimized digital twin to be close to the actual sorting effect of the sorting device, achieving a true reproduction of the actual sorting scene by the digital twin. The historical sorting plan includes multiple delivery directions set for the corresponding sorting shift and the corresponding slot allocation information for each delivery direction. The slot allocation information includes the number of slots allocated to the delivery direction and the location of each slot allocated to the delivery direction. A delivery direction is used to indicate a destination area for receiving parcels. One slot is assigned to one delivery direction. Of course, one delivery direction in the historical sorting plan can correspond to multiple slots.

[0090] The historical part supply data includes the logistics part information of all logistics parts delivered to the sorting equipment in the corresponding sorting shift, such as the receiving address of the logistics part, the weight of the logistics part, the volume of the logistics part, etc.

[0091] In operation 420, the delivery flow direction corresponding to each slot in the digital twin is determined according to the historical sorting plan. Then, the digital twin is fed with items according to the historical feeding data corresponding to the historical sorting plan, and the sorting process is simulated. The sorting result data obtained by simulating the sorting process of the digital twin based on the historical sorting plan and the historical feeding data is called the simulated sorting result data corresponding to the historical sorting plan.

[0092] Operation 430 : Adjust the parameters of the digital twin according to the historical sorting result data corresponding to the historical sorting plan and the simulated sorting result data corresponding to the historical sorting plan, until the fidelity of the digital twin reaches a fidelity threshold.

[0093] The historical sorting result data corresponding to the historical sorting plan refers to the actual sorting result data obtained when the sorting equipment performs sorting according to the historical sorting plan during the historical sorting shift when the sorting equipment supplies parts according to the historical sorting data.

[0094] Specifically, the historical sorting result data may include the drop-off data reflecting the logistics pieces dropped from each grid and the sorting efficiency parameters that overall reflect the sorting according to the historical sorting plan. The drop-off data is used to indicate the number of logistics pieces dropped from each grid in the sorting equipment. The sorting efficiency parameters can be the number of express parcels sorted per unit time, the sorting time, and the half-circle bag drop volume within the preset time. The fidelity of the digital twin is used to reflect the similarity between the sorting process simulated by the digital twin and the actual sorting process. In practice, if the similarity between the simulated sorting result data and the historical sorting result data obtained by actual sorting is higher, it indicates that the similarity between the simulated sorting process and the actual sorting process is higher. Therefore, in this application, the fidelity of the digital twin is determined based on the simulated sorting result data and the historical sorting result data. In some embodiments, the similarity between the simulated sorting result data and the historical sorting result data can be calculated, and the calculated similarity is used as the fidelity of the digital twin.

[0095] In operation 430, the fidelity of the digital twin can be determined based on the historical sorting result data corresponding to the historical sorting plan and the simulated sorting result data corresponding to the historical sorting plan. If the fidelity of the digital twin is lower than the fidelity threshold, the parameters of the digital twin are adjusted. The digital twin with the adjusted parameters then re-simulates the sorting process based on the historical sorting plan and historical infeed data, obtaining new simulated sorting result data and recalculating the fidelity of the digital twin. If the recalculated fidelity is still lower than the fidelity threshold, the parameters of the digital twin are further adjusted, and the sorting simulation and fidelity calculation operations are repeated until the recalculated fidelity reaches the fidelity threshold. The adjusted digital twin parameter may be the infeed speed.

[0096] In this application, the fidelity of the digital twin corresponding to the sorting equipment is optimized based on the historical sorting plan, historical supply data, and historical sorting result data corresponding to the sorting equipment, so that the optimized digital twin can accurately reproduce the sorting process on the sorting equipment, so that the subsequent use of the digital twin to simulate the sorting process is more accurate.

[0097] The sorting plan optimization method provided in this application, after obtaining the sorting efficiency parameters of the initial sorting plan, adjusts the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan, and performs sorting simulation on the intermediate sorting plan through a digital twin to obtain the sorting efficiency parameters of the intermediate logistics plan. This is repeated until the target sorting plan is obtained when the sorting efficiency parameters meet the preset conditions. In this way, the sorting efficiency parameters of the sorting plan are determined through the digital twin, and the sorting plan is updated and iterated according to the sorting efficiency parameters. This solves the problem of having no objective function and being unable to construct a data model to find the optimal solution, realizes the optimization of the sorting plan, and can improve the sorting efficiency of the sorting equipment.

[0098] The following describes an embodiment of the device of the present application, which can be used to perform the method described in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the above method embodiment of the present application.

[0099] FIG5 is a block diagram of a sorting plan optimization device according to an embodiment of the present application. The sorting plan optimization device can be configured in an electronic device to implement the sorting plan optimization method provided in the present application. As shown in FIG5 , the sorting plan optimization device includes:

[0100] The efficiency parameter acquisition module 810 is used to obtain the sorting efficiency parameters of the initial sorting plan;

[0101] A sorting plan adjustment module 820 is configured to adjust the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan;

[0102] An efficiency parameter determination module 830 is configured to perform a sorting simulation on the intermediate sorting plan based on the digital twin to obtain a sorting efficiency parameter of the intermediate sorting plan;

[0103] The sorting plan determination module 840 is used to obtain a target sorting plan when the sorting efficiency parameters meet preset conditions.

[0104] In some embodiments, the sorting plan adjustment module 820 is configured to: adjust sorting hyperparameters based on sorting efficiency parameters corresponding to the initial sorting plan to obtain adjusted sorting hyperparameters; the sorting hyperparameters include at least one of a maximum slot capacity, a minimum slot capacity, a ratio of infeeds to different infeed stations, and an average number of scans; and adjust the initial sorting plan based on the adjusted sorting hyperparameters to obtain an intermediate sorting plan.

[0105] In some embodiments, the sorting plan adjustment module 820 is configured to: adjust the number of slots and the slot area corresponding to the delivery directions in the initial sorting plan according to the adjusted sorting hyperparameters, thereby obtaining the target number of slots and the target slot area corresponding to each delivery direction in the initial sorting plan; and obtain an intermediate sorting plan based on the target number of slots and the target slot area corresponding to each delivery direction in the initial sorting plan.

[0106] In some embodiments, the sorting plan adjustment module 820 is used to: obtain the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan; match the delivery flow direction with the slots according to the target slot quantity and target slot area corresponding to each delivery flow direction in the initial sorting plan, the flow direction priority corresponding to each delivery flow direction in the initial sorting plan, and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, to obtain an intermediate sorting plan.

[0107] In some embodiments, the sorting plan adjustment module 820 is used to: determine the target slot priority corresponding to the flow direction priority corresponding to each delivery flow direction based on the correspondence between the slot priority and the flow direction priority; for each delivery flow direction, determine the pre-assigned slot for the delivery flow direction based on the target slot priority corresponding to the delivery flow direction; obtain the target slot corresponding to the delivery flow direction in the pre-assigned slots for the delivery flow direction based on the target slot area corresponding to the delivery flow direction and the number of target slots corresponding to the delivery flow direction; and obtain an intermediate sorting plan based on the target slots corresponding to each delivery flow direction.

[0108] In some embodiments, before obtaining the flow direction priorities corresponding to each delivery flow direction in the initial sorting plan and the slot priorities corresponding to each slot in the sorting device corresponding to the initial sorting plan, the sorting plan adjustment module 820 is configured to determine the slot priorities corresponding to each slot in the sorting device based on at least one of the distance between the slot and the printing device, the infeed corresponding to the slot, the distance between the slot and the turning position of the conveyor belt, and the distribution density of the bundling operation objects in the slot area where the slot is located.

[0109] In some embodiments, before obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting equipment corresponding to the initial sorting plan, the sorting plan adjustment module 820 is used to: determine the flow direction priority corresponding to each delivery flow direction based on at least one of the province type corresponding to each delivery flow direction, the timeliness type corresponding to each delivery flow direction, and the traffic type corresponding to each delivery flow direction.

[0110] In some embodiments, the efficiency parameter determination module 830 is used to: determine the target delivery flow direction corresponding to each grid on the sorting equipment according to the intermediate sorting plan; based on the digital twin, perform sorting simulation on the reference supply data according to the target delivery flow direction corresponding to each grid on the sorting equipment to obtain the sorting efficiency parameters corresponding to the intermediate sorting plan; the sorting efficiency parameters include sorting time, the number of express parcels sorted per unit time, and the half-circle bagging volume within the preset time.

[0111] In some embodiments, the sorting plan determination module 840 is configured to: if the sorting efficiency parameters of the intermediate sorting plan do not meet preset conditions, adjust the intermediate sorting plan according to the sorting efficiency parameters of the intermediate sorting plan to obtain a new intermediate sorting plan; perform sorting simulation on the new intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the new intermediate sorting plan; if the sorting efficiency parameters of the new intermediate sorting plan meet the preset conditions, determine the new intermediate sorting plan as the target sorting plan; if the sorting efficiency parameters of the new intermediate sorting plan do not meet the preset conditions, adjust the new intermediate sorting plan according to the sorting efficiency parameters of the new intermediate sorting plan, and iterate in this manner until sorting efficiency parameters that meet the preset conditions are obtained, and determine the sorting plan corresponding to the sorting efficiency parameters that meet the preset conditions as the target sorting plan.

[0112] In some embodiments, before performing sorting simulation on the intermediate sorting plan based on the digital twin and obtaining the sorting efficiency parameters of the intermediate sorting plan, the efficiency parameter determination module 830 is used to: construct a digital twin corresponding to the sorting device based on the structural information of the sorting device and the action mechanism information between different components in the sorting device; perform sorting simulation based on the historical sorting plan corresponding to the sorting device and the historical supply data corresponding to the historical sorting plan through the digital twin to obtain simulated sorting result data corresponding to the historical sorting plan; and adjust the parameters of the digital twin based on the historical sorting result data corresponding to the historical sorting plan and the simulated sorting result data corresponding to the historical sorting plan until the fidelity of the digital twin reaches a fidelity threshold.

[0113] Figure 6 is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. The electronic device can be used to execute the sorting plan optimization method provided in the present application. As shown in Figure 6, the electronic device may include: a processor 901, such as a CPU, a network interface 904, a user interface 903, a memory 905, and a communication bus 902. Among them, the communication bus 902 is used to realize the connection and communication between these components. The user interface 903 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and optionally, the user interface 903 may also include a standard wired interface and a wireless interface. The network interface 904 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 905 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk storage. The memory 905 may also be a storage device independent of the aforementioned processor 901.

[0114] Those skilled in the art will understand that the structure of the electronic device shown in FIG6 does not limit the electronic device, and may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0115] As shown in Figure 6 , memory 905, a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a program for implementing a sorting plan optimization method. In the electronic device shown in Figure 6 , network interface 904 is primarily used for communicating with other devices, such as the sorting device shown in Figure 1 . User interface 903 is primarily used to connect to and communicate data with a client (user end). Processor 901 can be used to invoke the program for implementing a sorting plan optimization method stored in memory 905 and execute the operations of the sorting plan optimization method described in any of the above method embodiments.

[0116] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor, the optimization method of the sorting plan in any of the above method embodiments is implemented. It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, etc., or any suitable combination of the above.

[0117] According to one aspect of an embodiment of the present application, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the optimization method of the sorting plan in any of the above method embodiments is implemented.

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiment of the present application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of a module or unit described above can be further divided into multiple modules or units to be concretized. Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiment of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present application. After considering the specification and practicing the embodiments disclosed here, those skilled in the art will easily think of other embodiments of the present application. This application is intended to cover any variants, uses or adaptive changes of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in this application. It should be understood that the present application is not limited to the precise structure described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is limited only by the appended claims.

Claims

1. A method for optimizing a sorting plan, the method comprising: Obtaining sorting efficiency parameters of the initial sorting plan; According to the sorting efficiency parameters of the initial sorting plan, the initial sorting plan is adjusted to obtain an intermediate sorting plan corresponding to the initial sorting plan; Performing sorting simulation on the intermediate sorting plan based on the digital twin to obtain sorting efficiency parameters of the intermediate sorting plan; and When the sorting efficiency parameters meet the preset conditions, the target sorting plan is obtained.

2. The method according to claim 1, wherein the initial sorting plan is adjusted according to the sorting efficiency parameter of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan, comprising: According to the sorting efficiency parameter corresponding to the initial sorting plan, the sorting super parameter is adjusted to obtain the adjusted sorting super parameter; the sorting super parameter includes at least one of the maximum capacity of the slot, the minimum capacity of the slot, the proportion of infeeds of different infeed stations, and the average number of scans; and The initial sorting plan is adjusted according to the adjusted sorting hyperparameters to obtain an intermediate sorting plan.

3. The method according to claim 2, wherein the initial sorting plan is adjusted according to the adjusted sorting hyperparameter to obtain an intermediate sorting plan, comprising: According to the adjusted sorting hyperparameters, the number of slots and the slot area corresponding to the delivery flow directions in the initial sorting plan are adjusted to obtain the target number of slots and the target slot area corresponding to each delivery flow direction in the initial sorting plan; and Based on the target slot numbers and target slot areas corresponding to each delivery flow direction in the initial sorting plan, an intermediate sorting plan is obtained.

4. The method according to claim 3, wherein the step of obtaining the intermediate sorting plan based on the target slot numbers and target slot areas corresponding to each delivery flow direction in the initial sorting plan comprises: Obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan; and According to the target slot quantity and target slot area corresponding to each delivery flow direction in the initial sorting plan, the flow direction priority corresponding to each delivery flow direction in the initial sorting plan, and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, the delivery flow directions are matched with the slots to obtain an intermediate sorting plan.

5. The method according to claim 4, wherein the process of matching the delivery directions with the slots according to the target slot number and target slot area corresponding to each delivery direction in the initial sorting plan, the direction priority corresponding to each delivery direction in the initial sorting plan, and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan to obtain the intermediate sorting plan comprises: According to the correspondence between the slot priority and the flow direction priority, determining the target slot priority corresponding to the flow direction priority corresponding to each of the delivery flow directions; For each delivery direction, according to the target slot priority corresponding to the delivery direction, determine the slot pre-allocated to the delivery direction; According to the target slot area corresponding to the delivery direction and the number of target slots corresponding to the delivery direction, the target slot corresponding to the delivery direction is obtained from the slots pre-allocated to the delivery direction; and Based on the target slots corresponding to the delivery directions, an intermediate sorting plan is obtained.

6. According to any one of the methods of claim 4 or 5, before obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, the method further comprises: The sorting device is determined according to at least one of the distance between the grid and the printing device, the supply table corresponding to the grid, the distance between the grid and the turning position of the conveyor belt, and the distribution density of the packaging operation objects in the grid area where the grid is located. The slot priority corresponding to each slot in the backup.

7. According to any one of the methods of claim 4 or 5, before obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, the method further comprises: The flow priority corresponding to each delivery direction is determined according to at least one of the province type corresponding to each delivery direction, the timeliness type corresponding to each delivery direction, and the traffic type corresponding to each delivery direction.

8. The method according to claim 1, wherein the sorting simulation of the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan comprises: According to the intermediate sorting plan, determine the target delivery flow direction corresponding to each slot on the sorting equipment; and Based on the digital twin, the reference supply data is sorted and simulated according to the target delivery flow direction corresponding to each grid on the sorting equipment to obtain the sorting efficiency parameters corresponding to the intermediate sorting plan; the sorting efficiency parameters include the sorting time, the number of express parcels sorted per unit time, and the half-circle bagging volume within the preset time.

9. The method according to claim 1, wherein when the sorting efficiency parameter satisfies a preset condition, obtaining a target sorting plan comprises: If the sorting efficiency parameter of the intermediate sorting plan does not meet the preset conditions, the intermediate sorting plan is adjusted according to the sorting efficiency parameter of the intermediate sorting plan to obtain a new intermediate sorting plan; Performing sorting simulation on the new intermediate sorting plan based on the digital twin to obtain sorting efficiency parameters of the new intermediate sorting plan; If the sorting efficiency parameter of the new intermediate sorting plan meets the preset conditions, the new intermediate sorting plan is determined as the target sorting plan; and If the sorting efficiency parameters of the new intermediate sorting plan do not meet the preset conditions, the new intermediate sorting plan is adjusted according to the sorting efficiency parameters of the new intermediate sorting plan, and the process is repeated until the sorting efficiency parameters that meet the preset conditions are obtained, and the sorting plan corresponding to the sorting efficiency parameters that meet the preset conditions is determined as the target sorting plan.

10. The method according to claim 1, before performing sorting simulation on the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan, the method further comprises: Constructing a digital twin corresponding to the sorting device according to the structural information of the sorting device and the action mechanism information between different components in the sorting device; Performing sorting simulation according to the historical sorting plan corresponding to the sorting device and the historical supply data corresponding to the historical sorting plan through the digital twin, so as to obtain simulated sorting result data corresponding to the historical sorting plan; and The parameters of the digital twin are adjusted according to the historical sorting result data corresponding to the historical sorting plan and the simulated sorting result data corresponding to the historical sorting plan until the fidelity of the digital twin reaches a fidelity threshold.

11. A sorting plan optimization device, the optimization device comprising: An efficiency parameter acquisition module is used to obtain the sorting efficiency parameters of the initial sorting plan; A sorting plan adjustment module, used to adjust the initial sorting plan according to the sorting efficiency parameters of the initial sorting plan to obtain an intermediate sorting plan corresponding to the initial sorting plan; An efficiency parameter determination module, used for performing sorting simulation on the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan; and The sorting plan determination module is used to obtain a target sorting plan when the sorting efficiency parameters meet preset conditions.

12. The device according to claim 11, wherein the sorting plan adjustment module is used to: According to the sorting efficiency parameters corresponding to the initial sorting plan, the sorting super parameters are adjusted to obtain the adjusted sorting super parameters; the sorting super parameters include the maximum capacity of the grid, the minimum capacity of the grid, the supply of different supply tables, At least one of the ratio and the average number of scans; and The initial sorting plan is adjusted according to the adjusted sorting hyperparameters to obtain an intermediate sorting plan.

13. The device according to claim 12, wherein the sorting plan adjustment module is used to: According to the adjusted sorting hyperparameters, the number of slots and the slot area corresponding to the delivery directions in the initial sorting plan are adjusted to obtain the target number of slots and the target slot area corresponding to each delivery direction in the initial sorting plan; and Based on the target slot numbers and target slot areas corresponding to each delivery flow direction in the initial sorting plan, an intermediate sorting plan is obtained.

14. The device according to claim 13, wherein the sorting plan adjustment module is used to: Obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan; and According to the target slot quantity and target slot area corresponding to each delivery flow direction in the initial sorting plan, the flow direction priority corresponding to each delivery flow direction in the initial sorting plan, and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, the delivery flow directions are matched with the slots to obtain an intermediate sorting plan.

15. The device according to claim 14, wherein the sorting plan adjustment module is used to: According to the correspondence between the slot priority and the flow direction priority, determining the target slot priority corresponding to the flow direction priority corresponding to each of the delivery flow directions; For each delivery direction, according to the target slot priority corresponding to the delivery direction, determine the slot pre-allocated to the delivery direction; According to the target slot area corresponding to the delivery direction and the number of target slots corresponding to the delivery direction, the target slot corresponding to the delivery direction is obtained from the slots pre-allocated to the delivery direction; and Based on the target slots corresponding to the delivery directions, an intermediate sorting plan is obtained.

16. The device according to any one of claims 14 or 15, before obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, the sorting plan adjustment module is used to: The slot priority corresponding to each slot in the sorting device is determined according to at least one of the distance between the slot and the printing device, the supply table corresponding to the slot, the distance between the slot and the turning position of the conveyor belt, and the distribution density of the packaging operation objects in the slot area where the slot is located.

17. The device according to any one of claims 14 or 15, before obtaining the flow direction priority corresponding to each delivery flow direction in the initial sorting plan and the slot priority corresponding to each slot in the sorting device corresponding to the initial sorting plan, the sorting plan adjustment module is used to: The flow priority corresponding to each delivery direction is determined according to at least one of the province type corresponding to each delivery direction, the timeliness type corresponding to each delivery direction, and the traffic type corresponding to each delivery direction.

18. The device according to claim 11, wherein the performance parameter determination module is configured to: According to the intermediate sorting plan, determine the target delivery flow direction corresponding to each slot on the sorting equipment; Based on the digital twin, the reference supply data is sorted and simulated according to the target delivery flow direction corresponding to each grid on the sorting equipment to obtain the sorting efficiency parameters corresponding to the intermediate sorting plan; the sorting efficiency parameters include the sorting time, the number of express parcels sorted per unit time, and the half-circle bagging volume within the preset time.

19. The device according to claim 11, wherein the sorting plan determination module is used to: If the sorting efficiency parameter of the intermediate sorting plan does not meet the preset conditions, the intermediate sorting plan is adjusted according to the sorting efficiency parameter of the intermediate sorting plan to obtain a new intermediate sorting plan; Performing sorting simulation on the new intermediate sorting plan based on the digital twin to obtain sorting efficiency parameters of the new intermediate sorting plan; If the sorting efficiency parameters of the new intermediate sorting plan meet the preset conditions, the new intermediate sorting plan Determine the target sorting plan; and If the sorting efficiency parameters of the new intermediate sorting plan do not meet the preset conditions, the new intermediate sorting plan is adjusted according to the sorting efficiency parameters of the new intermediate sorting plan, and the process is repeated until the sorting efficiency parameters that meet the preset conditions are obtained, and the sorting plan corresponding to the sorting efficiency parameters that meet the preset conditions is determined as the target sorting plan.

20. The device according to claim 11, before performing sorting simulation on the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan, the efficiency parameter determination module is used to: Constructing a digital twin corresponding to the sorting device according to the structural information of the sorting device and the action mechanism information between different components in the sorting device; Performing sorting simulation according to the historical sorting plan corresponding to the sorting device and the historical supply data corresponding to the historical sorting plan through the digital twin to obtain simulated sorting result data corresponding to the historical sorting plan; and The parameters of the digital twin are adjusted according to the historical sorting result data corresponding to the historical sorting plan and the simulated sorting result data corresponding to the historical sorting plan until the fidelity of the digital twin reaches a fidelity threshold.

21. An electronic device, comprising: processor; and A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the operations of the method according to any one of claims 1 to 10 are implemented.

22. A computer-readable storage medium having computer-readable instructions stored thereon, which, when executed by a processor, implement the operations of the method according to any one of claims 1 to 10.

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