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

Abstract

The invention relates to the technical field of logistics, and discloses a sorting plan optimization method and device, electronic equipment and a storage medium. After sorting efficiency parameters of an initial sorting plan are obtained, the initial sorting plan is adjusted according to the sorting efficiency parameters of the initial sorting plan, and an intermediate sorting plan corresponding to the initial sorting plan is obtained; and carrying out sorting simulation on the intermediate sorting plan through the digital twin body to obtain a sorting efficiency parameter of the intermediate logistics plan, repeating the steps, and obtaining a target sorting plan when the sorting efficiency parameter meets a preset condition. Therefore, the sorting efficiency parameters of the sorting plan are determined through digital twinning, and the sorting plan is updated and iterated according to the sorting efficiency parameters, so that the problems that no target function exists and a data model cannot be constructed to solve an optimal solution are solved, the optimization of the sorting plan is realized, and the sorting efficiency of the sorting equipment can be improved.

Description

Technical Field

[0001] The present application relates to the field of logistics technology, and more specifically, to an optimization method, device, electronic device and storage medium for a sorting plan. Background Art

[0002] 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 sorting logistics parts through the sorting equipment, it is necessary to formulate a sorting plan for the sorting equipment, that is, to assign delivery directions to the grids at various positions on the sorting equipment, where one 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.

[0003] However, due to the complexity of logistics scenarios, the 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 the sorting plan, it is difficult to obtain the optimal solution for the sorting plan using traditional optimization methods, thereby achieving optimization of the sorting plan. Summary of the invention

[0004] In view of the above problems, the embodiments of the present application propose a method, device, electronic device and storage medium for a sorting plan, so as to optimize the sorting plan and improve the sorting efficiency of the sorting device.

[0005] According to one aspect of an embodiment of the present application, a method for optimizing a sorting plan is provided, the method comprising:

[0006] Obtaining sorting efficiency parameters of the initial sorting plan;

[0007] 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;

[0008] Performing sorting simulation on the intermediate sorting plan based on the digital twin to obtain sorting efficiency parameters of the intermediate sorting plan;

[0009] When the sorting efficiency parameters meet the preset conditions, the target sorting plan is obtained.

[0010] According to one aspect of an embodiment of the present application, a device for optimizing a sorting plan is provided, comprising:

[0011] An efficiency parameter acquisition module is used to obtain the sorting efficiency parameters of the initial sorting plan;

[0012] 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;

[0013] 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;

[0014] The sorting plan determination module is used to obtain a target sorting plan when the sorting efficiency parameters meet preset conditions.

[0015] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: a processor; a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the optimization method of the sorting plan as described above is implemented.

[0016] 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 as described above is implemented.

[0017] 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 above-mentioned method for optimizing the sorting plan is implemented.

[0018] In this application, after obtaining the sorting efficiency parameters of the initial sorting plan, the initial sorting plan is adjusted according to the sorting efficiency parameters of the initial sorting plan to obtain the intermediate sorting plan corresponding to the initial sorting plan, and the intermediate sorting plan is sorted and simulated through the 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, 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 It is a schematic diagram of an application scenario of the present application according to an embodiment of the present application.

[0021] Figure 2 It is one of the flow charts of the optimization method of the sorting plan according to one embodiment of the present application.

[0022] Figure 3 This is the second flowchart of a method for optimizing a sorting plan according to an embodiment of the present application.

[0023] Figure 4 This is the third flowchart of a method for optimizing a sorting plan according to an embodiment of the present application.

[0024] Figure 5 It is a block diagram of a sorting plan optimization device according to an embodiment of the present application.

[0025] Figure 6 A schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application is shown. DETAILED DESCRIPTION

[0026] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0027] It should be noted that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0028] As described in the background technology, in the field of logistics, the sorting equipment deployed in the transfer yard is used to sort the logistics parts, that is, to classify and pack the logistics parts in different delivery areas for subsequent transportation. Before sorting the logistics parts by the sorting equipment, it is necessary to formulate a sorting plan for the sorting equipment, that is, to allocate the delivery flow direction for the grids at each position on the sorting equipment, wherein one delivery flow direction is used to indicate a destination area for receiving the 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.

[0029] However, due to the complexity of logistics scenarios, the diverse distribution of express parcels, the unavailability of labor efficiency data, and the lack of a standard objective function to evaluate the quality of sorting plans, it is difficult to optimize the sorting plans using traditional optimization methods.

[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 twinning to obtain the sorting efficiency parameters of the sorting plan. The sorting plan is updated and iterated according to the sorting efficiency parameters, 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] Figure 1 is a schematic diagram of an application scenario of the present application according to an embodiment of the present application, such as Figure 1 As shown, the application scenario includes an electronic device 110, a sorting device 120 and a sorting database 130, and the sorting device 120 is connected to the electronic device 110 through a wired or wireless network. The sorting database 130 can be deployed on the electronic device 110, or on other devices other than the electronic device 110. The electronic device 110 can be a server (such as a physical server, a cloud server, etc.), or other devices with certain computing capabilities. The sorting database 130 can be used to store historical sorting data of each sorting device, that is, the sorting-related data (such as historical sorting plans, historical supply data, and historical sorting result data) generated by the sorting device 120 in historical sorting shifts are stored in the sorting database 130. Furthermore, the sorting database 130 can also store the 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 steps are described below.

[0033] After determining the target sorting plan for the sorting device 120, the electronic device 110 may send the target sorting plan to the sorting device 120, so that the sorting device sets the delivery flow direction of the slots at each position according to the target sorting plan.

[0034] The implementation details of the technical solution of the embodiment of the present application are described in detail below:

[0035] Figure 2 is a flow chart 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, and the electronic device can be a server. Figure 2As shown, the method at least includes steps 210 to 240, which are described in detail as follows:

[0036] Step 210, obtaining the sorting efficiency parameters of the initial sorting plan;

[0037] In the present application, the initial sorting plan is a sorting plan to be optimized. In certain embodiments, the initial sorting plan can be formulated by the sorting staff according to their own work experience.

[0038] In the present application, the sorting plan is a plan formulated to improve the working efficiency of the sorting equipment. In the present application, the sorting plan may include the position of the slots assigned to each delivery flow direction and the number of slots assigned to each delivery flow direction.

[0039] In practice, the initial sorting plan may be unreasonable. For example, if the delivery direction of each slot on the sorting equipment is allocated according to the initial sorting plan, there may be a large difference in the number of dropped items between some different slots during the sorting process. This will result in the slots not being fully utilized, and the sorting efficiency of the sorting equipment according to the initial sorting plan will be low. Therefore, the initial sorting plan needs to be optimized.

[0040] In the present application, the sorting plan can be optimized based on the sorting efficiency parameters. Among them, the sorting efficiency parameters 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 can be, but are not limited to, one or more of the sorting time, the number of express parcels sorted per unit time, and the half-circle bagging volume within the preset time. The parameter of the half-circle bagging volume within the preset time is applicable to ring sorting equipment, which refers to the number of logistics pieces that fall from the grid within the preset time without exceeding half a circle on the ring sorting equipment.

[0041] In the present application, when the initial sorting plan is formulated by the sorting staff based on their own work experience, the sorting efficiency parameter of the initial sorting plan can be the production capacity of the actual site (such as the sorting equipment in the transfer yard) for implementing the initial sorting plan, or it can be the production capacity set by the sorting staff for the initial sorting plan.

[0042] Step 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.

[0043] In the present application, in the process of optimizing 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 the 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 the preset conditions are not met, the initial sorting plan is adjusted.

[0044] It can be understood 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.

[0045] Optionally, in the present application, the initial sorting plan is adjusted by adjusting the number of slots allocated to each delivery flow in the initial sorting plan.

[0046] Optionally, in the present application, when the number of slots of the slots allocated to each delivery flow in the initial sorting plan is adjusted, the number of slots of the slots of the slots allocated to each delivery flow in the initial sorting plan can be adjusted according to the set adjustment number. For example, at each adjustment, for each delivery flow, the number of slots of the slots allocated to the delivery flow can be increased by A, or decreased by A.

[0047] Optionally, in the present application, the initial sorting plan is adjusted, and the grid positions of the grids assigned to each delivery flow direction in the initial sorting plan may also be adjusted.

[0048] Optionally, in the present application, when adjusting the slot positions of the slots to which each delivery flow direction is assigned in the initial sorting plan, the slot positions of the slots to which each delivery flow direction is assigned in the initial sorting plan may be adjusted randomly, or the slot positions of the slots to which each delivery flow direction is assigned may be adjusted according to the supply areas corresponding to each delivery flow direction. For example, for each delivery flow direction, the supply areas of the delivery flow direction include area A and area B, then the slot positions of the slots to which the delivery flow direction is assigned may be adjusted to area A and area B. In the present application, after adjusting the initial sorting plan, the intermediate sorting plan corresponding to the initial sorting plan may be obtained.

[0049] It can be understood that the intermediate sorting plan is a sorting plan that is in the process of being optimized but has not been completely optimized.

[0050] Step 230: Perform sorting simulation on the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan.

[0051] 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.

[0052] Digital twin, also known as digital twin, is a digital mapping of physical objects. In this application, digital twin is a digital mapping of sorting equipment, and the digital twin is a dynamic simulation of sorting equipment. Therefore, the sorting efficiency parameters of the sorting plan can be accurately reflected through the digital twin.

[0053] In the present application, the sorting efficiency parameters of the sorting plan are determined by the digital twin, so that the sorting efficiency parameters of the sorting plan can be accurately obtained without implementing the sorting plan on the ground. In this way, the optimization efficiency of the sorting plan can be improved, and the accuracy of the sorting efficiency parameters can also be ensured.

[0054] Step 240, when the sorting efficiency parameter meets the preset conditions, a target sorting plan is obtained.

[0055] 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, the intermediate sorting plan will continue to be adjusted, that is, the number of slots of the slots allocated to each delivery flow in the intermediate sorting plan will continue to be adjusted 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, and then detect whether the sorting efficiency parameters of the adjusted intermediate sorting plan meet the preset conditions, so as to iterate until the sorting efficiency parameters of the intermediate sorting plan are adjusted to meet the preset conditions, and the intermediate sorting plan whose sorting efficiency parameters meet the preset conditions is determined as the target sorting plan.

[0056] In the present application, the preset condition may be that the sorting efficiency parameter reaches convergence, or that the sorting efficiency parameter is greater than a set sorting efficiency threshold, and there is no specific limitation.

[0057] It can be understood that in the present 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 allocates 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.

[0058] The optimization method of the sorting plan provided in the present 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, and repeats this process to obtain the target sorting plan 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, which solves the problem of no objective function and 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.

[0059] In view of the fact that the sorting plan will directly affect the sorting efficiency of the sorting equipment in practical applications, in order to optimize the sorting plan faster and better, in the present application, the initial sorting plan is adjusted according to the sorting efficiency parameters of the initial sorting plan, and the step of obtaining the intermediate sorting plan corresponding to the initial sorting plan may also include:

[0060] (1) According to the sorting efficiency parameters corresponding to the initial sorting plan, the sorting hyper-parameters are adjusted to obtain adjusted sorting hyper-parameters.

[0061] (2) According to the adjusted sorting hyperparameters, the initial sorting plan is adjusted to obtain an intermediate sorting plan.

[0062] In this application, the sorting super parameter refers to a parameter used to reflect the sorting distribution situation on the sorting equipment. The sorting super parameter includes at least one of the maximum capacity of the grid, the minimum capacity of the grid, the proportion of the infeeds of different infeed stations, and the average number of scans.

[0063] Among them, the maximum capacity of the grid refers to the maximum number of logistics items dropped from the grid; correspondingly, the minimum capacity of the grid refers to the minimum number of logistics items dropped from the grid. For the grids in the sorting equipment, if the grid capacities corresponding to different grids are quite different, for example, the grid capacity corresponding to a grid A is relatively large (that is, the number of express parcels dropped from the grid is relatively large), and the grid capacity corresponding to a grid B is relatively small (that is, the number of express parcels dropped from the grid is relatively small), it means that the number of grids allocated to the delivery flow corresponding to grid A is unreasonable, and the number of grids allocated to the delivery flow corresponding to grid B is unreasonable, resulting in a large difference in the number of parcels dropped from different grids. In this way, when the express parcel flows to grid A, the probability of grid locking (the grid will be locked after a bag is full, and then the packing personnel will open the grid after replacing the bag) is relatively high. In this way, the express parcel needs to continue to be transported on the conveyor belt and wait for the next transmission to the grid corresponding to the delivery flow.

[0064] 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 down. The supply ratio of different infeeds refers to the ratio 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 parcel is supplied from infeed P1, and Q2 parcels are supplied 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).

[0065] The number of scans of a parcel refers to the number of times the parcel passes through the six-sided scanning device before falling into the bag collection bag. For example, if the number of scans of 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 both times, indicating that the compartment corresponding to the delivery flow direction to which the logistics parcel belongs is locked (that is, the compartment is full at this time and is waiting for the bagging personnel to replace the bag collection bag). If the average number of scans of the parcels corresponding to a delivery flow direction is large, it means that the number of compartments 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 of all parcels in a sorting shift, or it can be counted by delivery flow direction, that is, the average number of scans of all parcels corresponding to each delivery flow direction in a sorting shift is counted.

[0066] Optionally, in the optimization of this sorting plan, the initial value of the sorting hyperparameter can be set by the staff, which is usually used for the formulation of sorting plans for newly built transfer stations. In the optimization of this sorting plan, the initial value of the sorting hyperparameter can also be the final value of the sorting hyperparameter determined during the last optimization, which is usually used for the optimization of sorting plans for transfer stations in use.

[0067] 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 according to 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.

[0068] For example, the ratio adjustment value relationship data includes a mapping relationship between ratio A and a adjustment value, and a mapping relationship between ratio B and b adjustment value. Assuming that 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 is A, the adjustment value of the sorting hyperparameter can be obtained as a, and then the sorting hyperparameter is adjusted according to the adjustment value a.

[0069] It can be understood that when the sorting hyperparameter includes multiple parameters, the adjustment value of the sorting hyperparameter includes the adjustment value of each parameter.

[0070] Optionally, when the sorting hyperparameter includes multiple parameters, when adjusting the value of the sorting hyperparameter, only one parameter may be adjusted each time, or multiple parameters may be adjusted simultaneously each time.

[0071] Optionally, in some embodiments of the present application, the value of the sorting hyperparameter can also be adjusted based on the set adjustment step size. If the optimal sorting plan needs to be found quickly, the adjustment step size can be set larger, and if the most accurate optimal sorting plan needs to be found, the adjustment step size can be set smaller. There is no specific limitation and it can be set according to actual needs.

[0072] After adjusting the value of the sorting hyperparameter, the adjusted sorting hyperparameter can be obtained. After obtaining the adjusted sorting hyperparameter, the initial sorting plan can be adjusted according to the adjusted sorting hyperparameter to obtain an intermediate sorting plan.

[0073] In the present application, when the initial sorting plan is adjusted according to the adjusted sorting hyperparameters, the number of slots and the slot positions corresponding to the delivery flow directions in the initial sorting plan may be adjusted. Therefore, in the present application, the initial sorting plan is adjusted according to the adjusted sorting hyperparameters, and the step of obtaining the intermediate sorting plan may also include:

[0074] (a1) According to the adjusted sorting hyperparameters, the number of slots and the slot area corresponding to the delivery flow direction 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.

[0075] (a2) 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.

[0076] The initial sorting plan includes the positions of the slots assigned to each delivery direction and the number of slots assigned to each delivery direction. Each slot belongs to a slot area, and the slot areas to which the slots belong can 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 supply table, slot B is located in the slot area of ​​the B supply table, and slot C is located in the slot area of ​​the A supply table.

[0077] Optionally, according to the adjusted sorting hyperparameters, the number of slots and the slot area corresponding to the delivery flow direction in the initial sorting plan are adjusted. The historical sorting data of the sorting equipment corresponding to the initial sorting plan can be obtained first. The historical sorting data includes the sorting information of each express delivery, including but not limited to the corresponding delivery flow direction, the corresponding delivery table and the number of scans, etc.

[0078] After obtaining the historical sorting data, the historical delivery volume corresponding to each delivery direction, the historical delivery ratio of different infeed stations, and the historical average scanning times of express parcels and other information can be determined based on the historical sorting data. Then, according to the adjusted sorting hyperparameters, the historical delivery volume corresponding to each delivery direction, the historical delivery ratio of different infeed stations, and the historical average scanning times of express parcels, the number of grid openings and the grid opening area corresponding to the delivery direction in the initial sorting plan are adjusted to obtain the target number of grid openings and the target grid opening area corresponding to each delivery direction in the initial sorting plan.

[0079] Among them, when adjusting the number of slots corresponding to the delivery flow direction in the initial sorting plan, for each delivery flow direction, the historical delivery volume corresponding to the delivery flow direction can be compared with the minimum capacity of the slot in the sorting hyperparameters. If the historical delivery volume corresponding to the delivery flow direction is less than the minimum capacity of the slot in the sorting hyperparameters, it indicates that the delivery volume corresponding to the delivery flow direction is small.

[0080] Considering the actual application, for each delivery flow, at least one slot will be allocated to the delivery flow to sort the express parcels of the delivery flow. Therefore, for each delivery flow, if the historical delivery volume corresponding to the delivery flow is less than the minimum capacity of the slot in the sorting hyperparameter, the number of slots corresponding to the delivery flow can be adjusted to 1, that is, the target number of slots corresponding to the delivery flow is 1.

[0081] For each delivery direction, if the historical delivery volume corresponding to the delivery direction is not less than the minimum capacity of the grid in the sorting hyperparameters, the historical delivery volume corresponding to the delivery direction is compared with the maximum capacity of the grid in the sorting hyperparameters. If the historical delivery volume corresponding to the delivery direction is not greater than the maximum capacity of the grid in the sorting hyperparameters, the number of grids allocated to the delivery direction can be reduced according to the set adjustment quantity to obtain the target number of grids 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 capacity of the grid in the sorting hyperparameters, but the number of grids corresponding to the delivery direction is 1, there is no need to reduce the number of grids corresponding to the delivery direction, that is, the target number of grids corresponding to the delivery direction is 1.

[0082] If the historical delivery volume corresponding to the delivery flow direction is greater than the maximum capacity of the grid in the sorting hyperparameter, the number of grids allocated to the delivery flow direction can be increased according to the set adjustment quantity to obtain the target number of grids corresponding to the delivery flow direction.

[0083] Considering the different environments and express delivery processing efficiencies of different slots in actual applications, different slots handle different express deliveries. For example, for a slot without printing equipment and staff nearby, once the slot is locked, the slot will not be able to handle express deliveries for a long time, resulting in a small amount of express deliveries processed. In this case, it is necessary to add more slots. For a slot with printing equipment and staff nearby, once the slot is locked, the lock state of the slot will be quickly resolved, so the impact on the express delivery volume is small. In this case, it is not necessary to add more slots.

[0084] When a grid is locked for a long time, the number of scans for parcels falling into the grid will increase. Therefore, in order to ensure the accuracy of the adjustment of the number of grids, in this application, for each delivery direction, when the historical delivery volume corresponding to the delivery direction is greater than the maximum capacity of the grid in the sorting hyperparameters, the historical average number of scans corresponding to the delivery direction can also be compared with the average number of scans in the sorting hyperparameters.

[0085] If the historical delivery volume corresponding to the delivery flow direction is greater than the maximum capacity of the grid in the sorting hyperparameters, and the historical average number of scans corresponding to the delivery flow direction is greater than the average number of scans in the sorting hyperparameters, then the number of grids assigned to the delivery flow direction is increased according to the set adjustment quantity to obtain the target number of grids corresponding to the delivery flow direction. If the historical delivery volume corresponding to the delivery flow direction is greater than the maximum capacity of the grid in the sorting hyperparameters, but the historical average number of scans corresponding to the delivery flow direction is not greater than the average number of scans in the sorting hyperparameters, then there is no need to adjust the number of grids corresponding to the delivery flow direction, and the number of grids corresponding to the delivery flow direction in the initial sorting plan is determined as the target number of grids corresponding to the delivery flow direction.

[0086] Among them, when adjusting the grid area corresponding to the delivery flow direction in the initial sorting plan, for each delivery flow direction, the historical supply ratio of each induction station corresponding to the delivery flow direction can be compared with the supply ratio of each induction station in the sorting hyperparameters, and the target induction station whose historical supply ratio is greater than the supply ratio of the corresponding induction station in the sorting hyperparameters is determined. After obtaining the target induction station, the grid area of ​​the target induction station can be determined as the target grid area of ​​the delivery flow direction. For example, for induction station A and induction station B, assuming that the supply ratio of induction station A in the sorting hyperparameters is x1, and the supply ratio of induction station B is x2, the historical supply ratio of a certain delivery flow direction at induction station A is y1, and the historical supply ratio at induction station B is y2, if y1 is greater than x1, and y2 is less than x2, then induction station A is determined as the target induction station, and the grid area of ​​induction station A is the target grid area of ​​the delivery flow direction.

[0087] It can be understood that for each delivery flow direction in the initial sorting plan, after obtaining the target grid opening number and target grid opening area corresponding to each delivery flow direction, for each delivery flow direction, a target grid opening number can be selected in the target grid opening area corresponding to the delivery flow direction as the target grid opening corresponding to the delivery flow direction. After obtaining the target grid opening corresponding to each delivery flow direction, the intermediate sorting plan can be obtained according to the target grid opening of each delivery flow direction.

[0088] In order to improve the accuracy of the slots corresponding to each delivery flow direction, in the present 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 step of obtaining the intermediate sorting plan can also include:

[0089] (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 device corresponding to the initial sorting plan.

[0090] (b2) According to 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 device corresponding to the initial sorting plan, the delivery flow directions are matched with the slots to obtain an intermediate sorting plan.

[0091] In some embodiments, before step 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.

[0092] After packing, the packing personnel need to use the printing device to print the logistics voucher corresponding to the corresponding bag. It can be understood that if the distance between the grid opening and the printing device is smaller, the packing personnel's moving distance is smaller, and the packing personnel do not need to spend more extra energy and time to print the logistics voucher. Therefore, it can be set that the larger the distance between the grid opening and the printing device, the higher the priority of the grid opening; conversely, the smaller the distance between the grid opening and the printing device, the lower the priority of the grid opening.

[0093] For express parcels, the closer the parcel is to the turning position of the conveyor belt, the more likely it is to float, causing the parcel to fall from other parcels. Therefore, the smaller the distance between the parcel and the turning position of the conveyor belt, the lower the priority, and the larger the distance between the parcel and the turning position of the conveyor belt, the higher the priority.

[0094] The distribution density of the packing operation objects in the grid area where the grid is located reflects the number of packing operation objects arranged in the grid area. Since the number of grids in the grid area is fixed, the number of grids that a single packing operation object (i.e., packing personnel) is responsible for can be determined according to the distribution density of the packing operation objects in the grid area where the grid is located. For a grid, if the grid is located in a grid area with a higher distribution density of packing operation objects, the priority of the grid is higher. Conversely, if the grid is located in a grid area with a lower distribution density of packing operation objects, the priority of the grid is lower.

[0095] The induction table is used to supply items to the slots in an area. Different induction tables are responsible for supplying items to different slot areas. It can be set that the more slots there are in the slot area that the induction table is responsible for supplying items to, the higher the slot priority in the slot area.

[0096] 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 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 objects of the packaging operation in the slot area where the slot is located, the step specifically includes: determining the first priority score corresponding to each slot according to the distance between the slot and the printing device; determining the second priority score corresponding to each slot according to the supply table corresponding to the slot; determining the third priority score corresponding to each slot according to the distance between the slot and the turning position of the conveyor belt; determining the fourth priority score corresponding to each slot according to the distribution density of the objects of the packaging operation in the slot area where the slot is located; 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, to determine the total 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.

[0097] In some embodiments, before step b1, the method further includes: determining the flow priority corresponding to each delivery direction based on 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.

[0098] The province types corresponding to the delivery flow include intra-province and extra-province. Generally, the grids corresponding to the delivery flow within the province are deployed together. For the delivery flow outside the province, the delivery flows of adjacent provinces are placed adjacent to each other, so as to avoid the long distance for re-delivery after the express delivery is wrongly sorted due to floating items. The priority of the delivery flow corresponding to the intra-province can be set higher than the priority of the delivery flow outside the province.

[0099] The time efficiency type corresponding to the delivery flow direction is used to indicate the time efficiency of the delivery flow direction. It can be set that the delivery flow direction with higher time efficiency requirements indicated by the corresponding time efficiency type has higher priority, and the delivery flow direction with lower time efficiency requirements has lower priority.

[0100] 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 a delivery flow direction with a large flow direction is higher than the priority of a delivery flow direction with a small flow direction.

[0101] 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 steps: 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, and determine the total 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 priority score, the second flow priority score, and the third flow priority score can be set according to actual needs and are not specifically limited here.

[0102] 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 device corresponding to the initial sorting plan, the delivery flow directions can be matched 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 the intermediate sorting plan.

[0103] In some embodiments, Figure 3 As shown, the corresponding slots of each delivery flow direction can be determined according to the following steps 310 to 340 to obtain the intermediate sorting plan. Specifically:

[0104] Step 310: According to the correspondence between the slot priority and the flow direction priority, determine the target slot priority corresponding to the flow direction priority corresponding to each delivery flow direction.

[0105] Step 320: for each delivery direction, determine the slot pre-allocated to the delivery direction according to the target slot priority corresponding to the delivery direction.

[0106] Step 330 , according to the target slot area corresponding to the delivery direction and the number of target slots corresponding to the delivery direction, obtain the target slot corresponding to the delivery direction from the slots pre-allocated to the delivery direction.

[0107] Step 340: Obtain an intermediate sorting plan based on the target slots corresponding to the delivery directions.

[0108] The correspondence between the grid priority and the flow priority can be set according to actual needs. For example, when the number of grid priority levels is the same as the number of flow priority levels, the grid priority of the same level can be set to correspond to the flow priority. Currently, it is not limited to this in practice. In a specific embodiment, a flow priority can correspond to one grid priority or multiple grid priorities.

[0109] It is understandable that in a sorting plan, the slots allocated to different delivery directions are not repeated, that is, during the allocation process, one slot on the sorting device corresponds to at most one delivery direction.

[0110] In step 320, for each delivery direction, the slot priority of each slot can be matched with the target slot priority corresponding to the delivery direction, and the slot whose slot priority is the target slot priority can be selected, and the selected slot whose slot priority is the target slot priority can be determined as the pre-allocated slot for the delivery direction.

[0111] For each delivery direction, after obtaining the pre-assigned grid openings for the delivery direction, you can select grid openings with a target number of grid opening areas as the target grid opening areas from the pre-assigned grid openings for the delivery direction based on the target grid opening area corresponding to the delivery direction and the target grid opening number corresponding to the delivery direction, and use the selected grid openings as the target grid openings corresponding to the delivery direction.

[0112] 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.

[0113] In some embodiments, in order to obtain more suitable and accurate grids for each delivery flow direction, in the present application, grid allocation constraints can also be set. According to the grid allocation constraints, the target grid area corresponding to the delivery flow direction, and the number of target grids corresponding to the delivery flow direction, the target grid corresponding to the delivery flow direction is obtained in the pre-allocated grids for the delivery flow direction.

[0114] Among them, the grid allocation constraint condition can be that for the same delivery direction, if multiple grids need to be allocated to the same delivery direction, then the multiple grids need to be allocated to the target grid areas corresponding to the delivery direction, and cannot be allocated to one target grid area; for example, if the L1 target grid area includes 50 grids and the L2 target grid area includes 70 grids, if a delivery direction needs to be allocated two grids, that is, the corresponding number of target grids is 2, then one of the grids allocated to the delivery direction is located in the L1 target grid area, and the other is located in the L2 target grid area.

[0115] Optionally, the slot allocation constraint can also be that for the same delivery flow, if multiple slots need to be allocated, then according to the set slot allocation ratio, some of the multiple slots need to be allocated to each target slot area corresponding to the delivery flow, and the remaining slots of the multiple 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 is 60 slots, if a delivery flow needs to be allocated 3 slots, assuming that the set slot allocation ratio is target slot area: other slot areas = 2:1, then the slots allocated to the delivery flow need to have 2 allocated in the target slot area and 1 allocated in the other slot area, that is, 2 are allocated in the L1 target slot area and the L2 target slot area, and 1 is allocated in the L3 slot area.

[0116] Optionally, the slot allocation constraints may also include constraints such as the number of consecutive slots in the same delivery direction does not exceed a quantity threshold, the slots corresponding to the corresponding delivery direction being a large flow direction cannot be consecutive, etc. These constraints may be set based on actual needs and are not specifically limited here.

[0117] After obtaining the target slots corresponding to the delivery directions, the intermediate sorting plan can be obtained based on the target slots corresponding to the delivery directions.

[0118] It can be understood that in the present application, after the intermediate sorting plan is obtained, the digital twin can be used to perform sorting simulation on the intermediate sorting plan to obtain the sorting efficiency parameters of the intermediate sorting plan.

[0119] 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 steps:

[0120] According to the intermediate sorting plan, determine the target delivery direction corresponding to each grid on the sorting equipment.

[0121] 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, and the sorting efficiency parameters corresponding to the intermediate sorting plan are obtained.

[0122] 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 device can be allocated according to the intermediate sorting plan. After that, 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 device. In this way, the sorting efficiency parameters corresponding to the intermediate sorting plan can be obtained.

[0123] The reference parcel data may be the parcel data of the sorting shift corresponding to the sorting plan, and the parcel data at least includes 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.

[0124] The sorting efficiency parameters corresponding to the sorting plan can be, but are not limited to, 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 sorting efficiency parameters can reflect the sorting efficiency corresponding to the sorting plan. If the sorting efficiency parameter is the sorting time, the shorter the sorting time, the higher the sorting efficiency; if the sorting efficiency parameter is the number of express parcels sorted per unit time, the more express parcels sorted per unit time, the higher the sorting efficiency; if the sorting efficiency parameter is the amount of bags dropped in half a circle within a preset time, the more bags dropped in half a circle within the preset time, the higher the sorting efficiency.

[0125] In some embodiments, if the sorting efficiency parameters include multiple items such as sorting time, the number of express parcels sorted per unit time, and the number of bags dropped in half a circle within a preset time, the sorting efficiency scores of the sorting plans corresponding to the various types of sorting efficiency parameters can be determined according to the various types of sorting efficiency parameters corresponding to the sorting plans, and the sorting efficiency scores of the sorting plans under multiple types of sorting efficiency parameters can be weightedly calculated to obtain the total sorting efficiency score corresponding to the sorting plans, and then the total sorting efficiency score can be used as the final sorting efficiency parameter.

[0126] 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, so as to obtain a target sorting plan whose sorting efficiency parameters meet the preset conditions. Optionally, this can be achieved by the following steps:

[0127] If the sorting efficiency parameters of the intermediate sorting plan do not meet the preset conditions, the intermediate sorting plan is adjusted according to the sorting efficiency parameters of the intermediate sorting plan to obtain a new intermediate sorting plan.

[0128] Based on the digital twin, the sorting simulation of the new intermediate sorting plan is carried out to obtain the sorting efficiency parameters of the new intermediate sorting plan.

[0129] 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.

[0130] 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 it is iterated 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.

[0131] 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 continued to be adjusted according to the sorting efficiency parameters of the intermediate sorting plan to obtain new adjusted sorting hyperparameters, and then the number of grids and the grid area corresponding to the delivery flow direction in the intermediate sorting plan are adjusted according to the new adjusted sorting hyperparameters to obtain a new intermediate sorting plan. Then, the new intermediate sorting plan is sorted and simulated by 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, and it 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.

[0132] Among them, the process of adjusting the adjusted sorting hyperparameters and the process of adjusting the number of grids and grid areas corresponding to the delivery flow direction in the intermediate sorting plan according to the new adjusted sorting hyperparameters, please refer to the above description and will not be repeated here.

[0133] 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 according to the sorting hyperparameters, the rationality of the number of grids and grid distribution corresponding to each delivery flow direction can be ensured, and the flow difference of different grids can be avoided to be too large. 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 the problem of low grid utilization due to the large difference in flow of different grids can be avoided; thereby, the sorting efficiency of the sorting equipment according to the optimized target sorting plan can be improved.

[0134] In some embodiments, Figure 4 As shown, in order to ensure the accuracy of the obtained sorting efficiency parameters and the accuracy of the final target sorting plan, the method further includes the following steps 410 to 430, which are described in detail as follows:

[0135] Step 410: construct 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.

[0136] The digital twin corresponding to the sorting device is a three-dimensional virtual model constructed based on the entity attribute data of each component in the sorting device and the action mechanism information between different components. In some embodiments, the digital twin corresponding to the sorting device can be constructed according to the process shown in the following steps A1 to A3, which are described in detail as follows:

[0137] Step A1, obtaining entity attribute data of each component in the sorting device.

[0138] Components in the sorting equipment include six-sided scanning equipment, induction tables, printing equipment, sorting conveyor belts, grids, etc. The entity attribute data of the component refers to the data reflecting the static attributes of the component, such as the size of the component and the physical attributes of the component (physical attributes such as the number of grids, the width of the grids, the spacing between the grids, etc.).

[0139] Step A2: Modeling is performed based on entity attribute data to obtain digital twin monomers of each component.

[0140] The digital twin monomer of the component is a three-dimensional virtual model of the component. In step A2, modeling can be performed based on the structural information (such as size, etc.) of the component to obtain the digital twin monomer of the component, which can be understood as a three-dimensional model of the component.

[0141] Step A3, according to 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.

[0142] The multiple components corresponding to the sorting equipment cooperate with each other to sort the express items. The action mechanism information between different components reflects the association relationship between different components, such as the relative position relationship between different entity objects, the action relationship between different entity objects, etc. Through the action mechanism information between different components, different digital twin monomers can be associated with each other, so that the obtained digital twin can reflect the action association relationship between different components corresponding to the sorting equipment, and the obtained digital twin corresponding to the sorting equipment can be used to simulate the dynamic sorting process of the sorting equipment.

[0143] Step 420: Perform 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.

[0144] In practice, the digital twin constructed for the sorting equipment may not accurately reproduce the sorting process of the sorting equipment. In this embodiment, in order to solve this problem, the fidelity of the digital twin corresponding to the sorting system is optimized based on the historical sorting data collected during the actual operation of the sorting equipment, so that the sorting effect of the optimized digital twin is close to the real sorting effect of the sorting equipment, so as to achieve the true restoration of the actual sorting scene by the digital twin.

[0145] The historical sorting plan includes multiple delivery directions set for the corresponding sorting shifts and the corresponding slot allocation information of each delivery direction, wherein the slot allocation information includes the number of slots allocated to the delivery direction and the position of each slot allocated to the delivery direction. A delivery direction is used to indicate a destination area. One slot is allocated to one delivery direction. Of course, one delivery direction in the historical sorting plan can correspond to multiple slots.

[0146] The historical supply data includes the logistics piece information of all logistics pieces delivered to the sorting equipment in the corresponding sorting shift, such as the receiving address of the logistics piece, the weight of the logistics piece, the volume of the logistics piece, etc.

[0147] In step 420, the delivery flow direction corresponding to each grid in the digital twin is determined according to the historical sorting plan. Afterwards, the digital twin is fed with 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.

[0148] Step 430 , adjusting 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.

[0149] 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 in the historical sorting shift when supplying parts according to the historical sorting data.

[0150] Specifically, the historical sorting result data may include the drop data reflecting the logistics pieces dropped from each grid and the sorting efficiency parameters reflecting the sorting according to the historical sorting plan. The drop 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 bagging volume within the preset time.

[0151] 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.

[0152] In step 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, and then the digital twin with the adjusted parameters re-simulates the sorting process according to the historical sorting plan and the historical supply data to obtain new simulated sorting result data, and recalculates the fidelity of the digital twin; if the recalculated fidelity is still lower than the fidelity threshold, the parameters of the digital twin are continued to be adjusted, and the above-mentioned sorting simulation and fidelity calculation steps are repeated until the recalculated fidelity reaches the fidelity threshold. The adjusted parameter of the digital twin can be the supply speed.

[0153] In the present 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 simulation of the sorting process using the digital twin is more accurate.

[0154] The optimization method of the sorting plan provided in the present 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, and repeats this process to obtain the target sorting plan 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, which solves the problem of no objective function and 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.

[0155] The following describes an apparatus embodiment of the present application, which can be used to execute the method in the above-mentioned embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the above-mentioned method embodiment of the present application.

[0156] Figure 5 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 by the present application. Figure 5 As shown, the optimization device of the sorting plan includes:

[0157] The efficiency parameter acquisition module 810 is used to acquire the sorting efficiency parameters of the initial sorting plan;

[0158] A sorting plan adjustment module 820, 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;

[0159] The efficiency parameter determination module 830 is used to perform sorting simulation on the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan;

[0160] The sorting plan determination module 840 is used to obtain a target sorting plan when the sorting efficiency parameters meet preset conditions.

[0161] In some embodiments, the sorting plan adjustment module 820 is used to:

[0162] According to the sorting efficiency parameters corresponding to the initial sorting plan, the sorting super parameters are adjusted to obtain adjusted sorting super parameters; the sorting super parameters include 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;

[0163] The initial sorting plan is adjusted according to the adjusted sorting hyperparameters to obtain an intermediate sorting plan.

[0164] In some embodiments, the sorting plan adjustment module 820 is used to:

[0165] According to the adjusted sorting hyperparameters, the number of slots and the slot area corresponding to the delivery flow direction 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;

[0166] Based on the target slot numbers and target slot areas corresponding to each delivery direction in the initial sorting plan, an intermediate sorting plan is obtained.

[0167] In some embodiments, the sorting plan adjustment module 820 is used to:

[0168] 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;

[0169] 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 equipment corresponding to the initial sorting plan, the delivery flow direction is matched with the slot to obtain the intermediate sorting plan.

[0170] In some embodiments, the sorting plan adjustment module 820 is used to:

[0171] According to the corresponding relationship between the slot priority and the flow direction priority, determine the target slot priority corresponding to the flow direction priority corresponding to each delivery flow direction;

[0172] For each delivery flow direction, determine the pre-allocated slot for the delivery flow direction according to the target slot priority corresponding to the delivery flow direction;

[0173] According to the target slot area corresponding to the delivery flow direction and the number of target slots corresponding to the delivery flow direction, the target slot corresponding to the delivery flow direction is obtained from the slots pre-allocated to the delivery flow direction;

[0174] Based on the target slots corresponding to each delivery direction, the intermediate sorting plan is obtained.

[0175] 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 device corresponding to the initial sorting plan, the sorting plan adjustment module 820 is used to:

[0176] 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.

[0177] 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 device corresponding to the initial sorting plan, the sorting plan adjustment module 820 is used to:

[0178] The flow priority corresponding to each delivery direction is determined based on 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.

[0179] In some embodiments, the performance parameter determination module 830 is used to:

[0180] According to the intermediate sorting plan, determine the target delivery flow direction corresponding to each slot on the sorting equipment;

[0181] 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.

[0182] In some embodiments, the sorting plan determination module 840 is used to:

[0183] If the sorting efficiency parameters of the intermediate sorting plan do not meet the preset conditions, the intermediate sorting plan is adjusted according to the sorting efficiency parameters of the intermediate sorting plan to obtain a new intermediate sorting plan;

[0184] Based on the digital twin, a new intermediate sorting plan is sorted and simulated to obtain the sorting efficiency parameters of the new intermediate sorting plan;

[0185] 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;

[0186] 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 it is iterated 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.

[0187] 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:

[0188] According to the structural information of the sorting equipment and the action mechanism information between different components in the sorting equipment, the digital twin corresponding to the sorting equipment is constructed;

[0189] The digital twin is used to perform sorting simulation according to the historical sorting plan corresponding to the sorting equipment and the historical supply data corresponding to the historical sorting plan, so as to obtain the simulated sorting result data corresponding to the historical sorting plan;

[0190] 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.

[0191] Figure 6 1 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 optimization method of the sorting plan provided by the present application. Figure 6 As shown, 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 memory. The memory 905 may optionally be a storage device independent of the aforementioned processor 901.

[0192] Those skilled in the art will understand that Figure 6 The structure of the electronic device shown in the figure does not constitute a limitation of the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0193] like Figure 6 As shown, the memory 905 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module, and a program for implementing the optimization method of the sorting plan. Figure 6 In the electronic device shown, the network interface 904 is mainly used to communicate with other devices, such as Figure 1 The user interface 903 is mainly used to connect to the client (user end) and perform data communication with the client; and the processor 901 can be used to call the program for implementing the optimization method of the sorting plan stored in the memory 905, and execute the steps of the optimization method of the sorting plan in any of the above method embodiments.

[0194] 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.

[0195] 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 two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, 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 disk 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, which can be used by an instruction execution system, a device or a device or used in combination with it. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as a part of a carrier wave, wherein a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs 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.

[0196] 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.

[0197] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order 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 a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0198] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0199] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods 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, and includes 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 implementation methods of the present application.

[0200] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations 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 the present application.

[0201] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for optimizing a sorting plan, characterized in that: The method comprises: 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; When the sorting efficiency parameters meet the preset conditions, the target sorting plan is obtained.

2. The method according to claim 1, characterized in that: The step of 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 includes: 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 the infeeds of different infeed stations, and the average number of scans; 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, characterized in that The step of adjusting the initial sorting plan according to the adjusted sorting hyperparameters to obtain an intermediate sorting plan includes: 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; 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, characterized in that 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 includes: 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; 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, characterized in that According to 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 device corresponding to the initial sorting plan, the delivery flow direction is matched with the slot to obtain the intermediate sorting plan, including: 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; Based on the target slots corresponding to the delivery directions, an intermediate sorting plan is obtained.

6. The method according to claim 4 or 5, characterized in that: 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 includes: 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.

7. The method according to claim 4 or 5, characterized in that: 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 includes: 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, characterized in that: The sorting simulation of the intermediate sorting plan based on the digital twin to obtain the sorting efficiency parameters of the intermediate sorting plan includes: 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.

9. The method according to claim 1, characterized in that: When the sorting efficiency parameter meets the preset conditions, a target sorting plan is obtained, including: 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; 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, characterized in that 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 includes: 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; 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 device for optimizing a sorting plan, characterized in that: The optimization device comprises: 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; The sorting plan determination module is used to obtain a target sorting plan when the sorting efficiency parameters meet preset conditions.

12. An electronic device, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 10 is implemented.

13. A computer-readable storage medium having computer-readable instructions stored thereon, characterized in that: When the computer-readable instructions are executed by a processor, the method according to any one of claims 1 to 10 is implemented.

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