Sorting plan generation method, electronic device, storage medium, and program product

Abstract

Provided in the present application are a sorting plan generation method, an electronic device, a storage medium, and a program product. The method comprises: acquiring an optimized sorting plan of a target sorting apparatus in a target shift of a target transit depot; performing logical function verification and simulation performance verification on the acquired optimized sorting plan to obtain a target verification result; and, on the basis of the target verification result, obtaining a new sorting plan. Thus, on the basis of performing logical function verification on the optimized sorting plan, performance verification of the optimized sorting plan is performed by means of simulation, such that rapid and low-cost verification of a service result, i.e., the optimized sorting plan, is achieved, thereby reducing the risk of site application, obtaining various key indicators for the performance of the optimized sorting plan, and assisting the transit depot in achieving optimization on timeliness, resources, productivity, quality, etc.

Description

Sorting plan generation methods, electronic devices, storage media, and software products Technical Field

[0001] This application relates to the field of logistics technology, specifically to a sorting plan generation method, electronic equipment, storage medium, and program product. Background Technology

[0002] Currently, when generating a new sorting plan for small parcels, a script is typically written to perform simple logical and functional checks on the new plan to determine its usability. The sorting efficiency of the plan, however, usually requires manual uploading to the production system for actual verification on the small parcel sorting machine at the transit point.

[0003] However, verifying the effectiveness of the sorting plan on the sorting machine itself is lagging. If the sorting plan is not effective, it will affect production efficiency and may lead to production accidents. The verification cost is high. In order to adapt to the ever-changing number and flow of packages in the transit area, it is necessary to modify or develop a new version of the sorting plan in a timely manner, which will further increase the verification cost. Summary of the Invention

[0004] Based on the defects and shortcomings of the existing technology, this application proposes a sorting plan generation method, electronic device, storage medium, and program product, which can perform logical function verification and simulation performance verification of the optimized sorting plan, obtain target verification results, generate and output a verification report based on the target verification results, realize low-cost and rapid verification of the logical function and performance of the optimized sorting plan, reduce site application risks, and solve the problems of the lag in sorting plan verification, the risk of causing safety accidents, and the high verification cost.

[0005] According to a first aspect of the embodiments of this application, a sorting plan generation method is provided, comprising: obtaining an optimized sorting plan for a target sorting device in a target shift of a target transfer station; then, performing logical function verification and simulation performance verification on the optimized sorting plan to obtain a target verification result; and finally, obtaining a new sorting plan based on the target verification result.

[0006] According to one embodiment of this application, obtaining an optimized sorting plan for a target sorting device in a target shift at a target transit hub includes: obtaining an initial sorting plan for the target sorting device in the target shift at the target transit hub; constructing a request message body based on the target transit hub, the target shift, and the target sorting device, combined with constraints, and generating a sorting plan optimization request, the sorting plan optimization request including the request message body; and, based on the sorting plan optimization request, calling a small item sorting plan optimization service to optimize the initial sorting plan to obtain an optimized sorting plan.

[0007] According to one embodiment of this application, the optimized sorting plan is subjected to logical function verification and simulation performance verification to obtain a target verification result, including: performing logical function verification on the optimized sorting plan to obtain a first verification result; if the first verification result indicates that the optimized sorting plan passes the logical function verification, then performing simulation performance verification on the optimized sorting plan based on the target simulation model to obtain a second verification result, wherein the target simulation model is a simulation model of the target transfer area; and generating a target verification result based on the first verification result and the second verification result, wherein the target verification result includes the first verification result and the second verification result.

[0008] According to one embodiment of this application, the optimized sorting plan is subjected to logical function verification and simulation performance verification to obtain a target verification result, and the method further includes: if the first verification result indicates that the optimized sorting plan has not passed the logical function verification, then a target verification result is generated based on the first verification result.

[0009] According to one embodiment of this application, a logical function verification is performed on an optimized sorting plan to obtain a first verification result, including: obtaining packaging rules and statistically analyzing the compartment information and tag information in the initial sorting plan, wherein the compartment information includes the compartment flow direction and compartment type; determining whether the optimized sorting plan conforms to the packaging rules and constraints, and whether the optimized sorting plan is missing compartment information and tag information, to obtain the first verification result; wherein, when the optimized sorting plan conforms to the packaging rules and constraints, and the optimized sorting plan is not missing compartment information and tag information, the first verification result indicates that the optimized sorting plan has passed the logical function verification.

[0010] According to one embodiment of this application, the simulation performance verification of the optimized sorting plan is performed based on the target simulation model to obtain a second verification result, including: performing simulated sorting based on the target simulation model, combined with small package data, package creation rules and the optimized sorting plan, to obtain target simulated sorting data, wherein the small package data includes the scanning order and package information of the small packages; calculating target simulated sorting indicators based on the target simulated sorting data; and generating a second verification result based on the target simulated sorting indicators, wherein the second verification result includes the target simulated sorting indicators.

[0011] According to one embodiment of this application, based on a target simulation model, combined with small parcel data, bagging rules and optimized sorting plan, simulated sorting is performed to obtain target simulated sorting data. This includes: inputting the parcel information from the small parcel data into the target simulation model in the scanning order, along with the optimized sorting plan and bagging rules, to simulate the sorting process of small parcels, and recording the sorting data of the small parcels passing through each node to obtain target simulated sorting data. The sorting data includes flow direction, scanning time, bag placement time, bag placement compartment, and bag tying time.

[0012] According to one embodiment of this application, the simulation performance verification of the optimized sorting plan based on the target simulation model to obtain a second verification result further includes: performing simulated sorting based on the target simulation model, combined with small package data, package creation rules and the initial sorting plan, to obtain initial simulated sorting data; calculating initial simulated sorting indicators based on the initial simulated sorting data; and adding the initial simulated sorting indicators to the second verification result.

[0013] According to one embodiment of this application, the simulation performance verification of the optimized sorting plan is performed based on the target simulation model to obtain a second verification result, which further includes: comparing the initial simulation sorting index with the target simulation sorting index to obtain a comparison result; and adding the comparison result to the second verification result.

[0014] According to one embodiment of this application, the small package data includes actual bagging data of small packages, the initial simulation sorting data includes simulated bagging data, and the verification report includes model distortion, which is the distortion of the target simulation model. Before verifying the simulation performance of the optimized sorting plan based on the target simulation model to obtain a second verification result, the method further includes: based on the actual bagging data, counting the actual number of packages bagged in each compartment; based on the simulated bagging data, counting the simulated number of packages bagged in each compartment; for each compartment, determining the compartment distortion based on the ratio of the difference between the simulated number of packages bagged and the actual number of packages bagged to the actual number of packages bagged; summing the compartment distortion of all compartments to determine the model distortion; and further includes adding the model distortion to the second verification result to verify the simulation performance of the optimized sorting plan based on the target simulation model.

[0015] According to one embodiment of this application, after determining the sum of the grid distortion of all grids as the model distortion, the method further includes: if the model distortion is greater than a preset distortion threshold, then the operation of performing simulation performance verification of the optimized sorting plan based on the target simulation model to obtain a second verification result is not performed, and the model distortion is used as the second verification result; if the model distortion is not greater than the preset distortion threshold, then the operation of performing simulation performance verification of the optimized sorting plan based on the target simulation model to obtain a second verification result is performed, and the model distortion is added to the second verification result.

[0016] According to one embodiment of this application, the method further includes: generating and outputting a verification report based on the target verification results, wherein generating and outputting a verification report based on the target verification results includes: if the target verification results of the optimized sorting plan for each target sorting device in each target shift of each target transfer station are determined, then a verification report is generated and output based on all target verification results.

[0017] According to a second aspect of the embodiments of this application, a sorting plan generation apparatus is provided, comprising: an acquisition module for acquiring an optimized sorting plan for a target sorting device in a target shift at a target transfer station; then, a verification module for performing logical function verification and simulation verification on the optimized sorting plan; and finally, a plan generation module for obtaining a new sorting plan based on the target verification results.

[0018] According to a third aspect of the embodiments of this application, an electronic device is provided, including a memory and a processor; the memory is connected to the processor and is used to store a program; the processor is used to implement the sorting plan generation method as described in the first aspect by running the program in the memory.

[0019] According to a fourth aspect of the embodiments of this application, a storage medium is provided, on which a computer program is stored, and when the computer program is run by a processor, it implements the sorting plan generation method as described in the first aspect.

[0020] According to a fifth aspect of the embodiments of this application, a computer program product is provided, the computer program product including computer program instructions, which, when executed by a processor, cause the processor to perform the sorting plan generation method as described in the first aspect.

[0021] The aforementioned sorting plan generation method, electronic equipment, storage medium, and program products can obtain the optimized sorting plan of the target sorting equipment in the target shift of the target transfer center, perform logical function verification and simulation performance verification on the obtained optimized sorting plan, obtain the target verification result, and obtain a new sorting plan based on the target verification result. Thus, based on the logical function verification of the optimized sorting plan, the performance of the optimized sorting plan is verified through simulation, realizing rapid and low-cost verification of business results, i.e., the optimized sorting plan, reducing site application risks, obtaining various key indicators of the performance of the optimized sorting plan, and thus assisting the transfer center in achieving optimization of timeliness, resources, output, and quality. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0023] Figure 1 is a flowchart illustrating a sorting plan generation method according to an embodiment of this application.

[0024] Figure 2 is a schematic diagram of a sorting plan generation process according to an embodiment of this application.

[0025] Figure 3 is a schematic diagram of a sorting plan generation device proposed in an embodiment of this application.

[0026] Figure 4 is a schematic diagram of the structure of an electronic device proposed in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] Overview

[0029] The small parcel sorting plan defines the mapping relationship between the sorting slots and flow directions on the sorting equipment in each shift of the transit area. During the sorting process, parcels are sequentially fed onto the conveyor belt. When they reach a slot that meets the requirements, the sorting equipment places the parcel down into the slot, completing the bagging (also known as sorting). In this way, parcels with the same flow direction can be grouped together.

[0030] As described in the background section, when sorting small parcels and generating a new sorting plan, scripts are typically written to logically and functionally validate the plan and determine its usability. The effectiveness of this sorting plan then needs to be manually uploaded to the production system for actual verification on the small parcel sorting machine at the transit point. However, this on-site verification of the sorting plan's effectiveness is lagging. If the plan's effectiveness is unsatisfactory, it will affect production efficiency and may even pose a risk of production accidents. Verification costs are high, and to adapt to the constantly changing parcel volume and flow distribution at the transit point, new versions of the sorting plan need to be modified or developed in a timely manner, further increasing verification costs.

[0031] Building upon this foundation, the inventors further discovered that verifying the efficiency of sorting plans through simulation, without the need for physical sorting machines, can significantly reduce verification costs, minimize the impact on production efficiency, and prevent production accidents. Therefore, after obtaining the optimized sorting plan for the target sorting equipment in the target shift at the target transfer station, the optimized sorting plan undergoes logical function verification and simulation efficiency verification. The resulting verification results are then used to generate and output a verification report.

[0032] Based on the above concept, this specification provides a sorting plan generation method, which will be described exemplarily below with reference to the accompanying drawings.

[0033] Exemplary methods

[0034] Referring to Figure 1, in an exemplary embodiment, a sorting plan generation method (which may include a sorting plan verification method) is provided, applied to any electronic device, which can obtain the sorting plans of each sorting device for each shift in each transfer station. As shown in Figure 1, the sorting plan generation method includes steps S101-S103.

[0035] S101: Obtain the optimized sorting plan for the target sorting equipment in the target shift of the target transit area.

[0036] In this context, the target transit area is any one of the transit areas, the target shift is any one of the shifts in the target transit area, and the target sorting equipment is any one of the sorting equipment in the target transit area. The optimized sorting plan is the sorting plan obtained by optimizing the original / initial sorting plan of the target sorting equipment in the target shift of the target transit area.

[0037] The shifts correspond to the sorting time periods.

[0038] In addition, the sorting equipment is a small-item sorting equipment, and the sorting plan is a plan for sorting small packages.

[0039] Obtain the initial sorting plan of the target sorting equipment in the target shift of the target transfer station, and optimize the initial sorting plan to obtain the optimized sorting plan.

[0040] Specifically, the initial sorting plan of the target sorting equipment in the target shift of the target transfer center is obtained. Based on the target transfer center, target shift and target sorting equipment, a request message body is constructed in combination with constraints, and a sorting plan optimization request is generated. The small item sorting plan optimization service is called to optimize the initial sorting plan and obtain the optimized sorting plan.

[0041] The sorting plan optimization request includes a request message body.

[0042] More specifically, by calling a third-party system interface, the initial sorting plan JSON message of the target sorting equipment under the target shift in the target transit area can be obtained and stored as a file to obtain the corresponding initial sorting plan. The initial sorting plan JSON message represents the specific initial sorting plan, which specifies the flow direction, timeliness, packaging label, and type of each sorting slot.

[0043] The package label is the information of a package obtained by creating multiple small packages based on the package creation rules.

[0044] The sorting slots are categorized as direct sorting slots, mixed sorting slots, or return sorting slots. Direct sorting slots correspond to a single flow direction, mixed sorting slots correspond to multiple flow directions, and return sorting slots are used to receive packages that failed to be properly bagged. Understandably, packages sent to the small-item sorting machine, if they fail to be properly bagged for some reason, will circulate on the conveyor belt more than a preset number of times before falling into the return sorting slot. Packages in the return sorting slot will be sorted again. The sorting method during this second sorting is either sorting by the small-item sorting machine or manual sorting.

[0045] More specifically, the request body is typically sent in a structured format, such as JSON or XML. The format of the request body corresponds to the content-type field in the request header, conveying all content except the request header. If the content-type field is JSON, then the content in the request body is in JSON format.

[0046] Generally, the request message body format follows the message body format defined by the interface of the device under test (DUT) that provides small item sorting optimization services. If the message body format defined by the interface of the DUT is JSON, the request message body is constructed according to the definition in the interface documentation of the DUT, and a request containing the request message body is sent to the DUT.

[0047] The fields defined in the interface of the device under test include: basic information fields and constraint fields.

[0048] Specifically, the basic information fields include site (transfer station) code, shift identifier (ID), shift name, sorting equipment identifier, and sorting plan version (sorting plan version number), which can be mapped to the transfer station, shift, sorting equipment, and corresponding initial sorting plan.

[0049] The constraint fields include specifying the list of return grids, specifying unchangeable labels, and specifying grids whose flow direction cannot be changed.

[0050] More specifically, sorting plan optimization requests can be sent to the device under test via, for example, HTTP communication.

[0051] More specifically, after generating a sorting plan optimization request, the sorting plan optimization request is input into the test piece, which optimizes the initial sorting plan and outputs the corresponding optimized sorting plan.

[0052] Alternatively, when obtaining the initial sorting plan for the target sorting equipment of the target shift in the target transit center, you can first obtain the initial sorting plan for each sorting equipment of each shift in each transit center, and then determine the initial sorting plan for the target sorting equipment of the target shift in the target transit center according to the transit center, shift and sorting equipment.

[0053] It should also be noted that the correspondence between the aforementioned transit areas, shifts, sorting equipment, and initial sorting plans can be stored in the site shift information file. The information in this site shift information file can be obtained by analyzing and summarizing small parcel data. This small parcel data includes data from a series of stages such as scanning, unpacking, loading, and bagging (sorting).

[0054] Due to the massive volume of daily parcel data across the entire network's transit hubs, and the diverse types of parcels including small parcels, large parcels, irregularly shaped parcels, and chilled parcels, the data processing module can collect, extract, and process data from these parcels.

[0055] Generally, data related to small parcels at various transit points can be filtered and selected from the base tables of the big data platform (BDP), which are the basic or underlying data tables on the BDP used to store logistics big data.

[0056] The data recording process for small parcels can be as follows: After a small parcel is placed in a bag and transported to a transit point, the bag tag is scanned, and the information of all small parcels in the bag is entered into the system, recording the arrival time and location of each small parcel at the transit point. After scanning, the bag is unpacked, the small parcels are removed, and transported to the vicinity of the small parcel sorting machine. Then, the small parcels are sent to the feeding platform and conveyed to the small parcel sorting machine via a conveyor belt. The feeding platform automatically scans the QR code of the small parcel (or scans it manually), recording the time of loading. Next, the small parcel is transported by the conveyor belt to a designated slot, where a wheel on the conveyor belt places the small parcel into a bag below the slot, completing the bag placement. Once the bag is full, it is tied (or a bagging, packing, or assembly operation is performed), and a new bag is placed below the slot, recording the bag placement time, the slot placement, and the tying time of the small parcel.

[0057] Since the shifts correspond to the sorting time periods, the small parcel data can be divided into shifts based on the sorting time periods and the node time data recorded in the small parcel data mentioned above.

[0058] S102: Perform logical function verification and simulation performance verification on the optimized sorting plan to obtain the target verification results.

[0059] Generally, the optimized sorting plan is first logically and functionally verified, and then its performance is verified by simulation. That is, the performance of the optimized sorting plan is verified by simulation to obtain the target verification result of the optimized sorting plan.

[0060] This involves both logical and functional verification of the optimized sorting plan, specifically verifying whether the optimized sorting plan can successfully complete the package sorting process. Generally, logical and functional verification are performed together.

[0061] The optimized sorting plan is validated through simulation. This involves performing simulated sorting according to the optimized plan using a target simulation model to obtain the plan's performance indicators. The target simulation model is the simulation model of the target transfer area corresponding to the optimized sorting plan, and the performance indicators reflect the sorting effectiveness of the optimized plan.

[0062] Specifically, before simulating the effectiveness of the optimized sorting plan, a target simulation model must be obtained based on the target transfer site corresponding to the optimized sorting plan.

[0063] The target simulation model can be constructed as follows: using appropriate modeling tools, such as AnyLogic, the small item sorting machine in the target transfer area is completely replicated into the virtual world through simulation modeling technology. Based on the operation process of the small item sorting machine in the transfer area, the sorting control logic of the small item sorting machine, the loading speed of the loading station, and the operation process of relevant personnel, a digital twin simulation model of the small item sorting machine, loading station, belt conveyor, and various personnel in the transfer area is built to obtain the target simulation model.

[0064] Among them, a suitable modeling tool can be selected based on the sorting logic and data complexity of the sorting equipment (i.e., small item sorting equipment) in the target transfer area.

[0065] Of course, simulation models for other transit points can also be constructed using this process.

[0066] Alternatively, specifically, before simulating and verifying the effectiveness of the optimized sorting plan, the simulation models of each transfer station are obtained first. Then, based on the target transfer station corresponding to the optimized sorting plan, the simulation model corresponding to the target transfer station is determined from the simulation models of each transfer station, i.e., the target simulation model.

[0067] Understandably, the simulation models of the aforementioned transit hubs, including the simulation model of the target transit hub, can be stored locally.

[0068] S103: Based on the target verification results, obtain a new sorting plan.

[0069] Specifically, in order to adapt to the ever-changing number and flow of parcels in the transit center, a new sorting plan can be generated based on the target verification results. The new sorting plan (i.e., the optimized sorting plan) can be understood as a new sorting plan that has been verified (i.e., the target verification results) to be feasible and superior to the current plan.

[0070] In one embodiment, a verification report is generated and output based on the target verification results.

[0071] The verification report includes the target verification results.

[0072] The target verification result is the result of logical function verification and simulation performance verification of the optimized sorting plan. It can characterize whether the optimized sorting plan can complete the package sorting and the effect of package sorting.

[0073] In this embodiment, by obtaining the optimized sorting plan of the target sorting equipment in the target shift of the target transit center, the obtained optimized sorting plan is subjected to logical function verification and simulation performance verification to obtain the target verification result. Based on the target verification result, a new sorting plan is obtained. Thus, on the basis of logical function verification of the optimized sorting plan, the performance of the optimized sorting plan is verified by simulation, thereby realizing the rapid and low-cost verification of the business result, i.e., the optimized sorting plan, reducing the risk of site application, obtaining various key indicators of the performance of the optimized sorting plan, and assisting the transit center in achieving optimization of timeliness, resources, capacity and quality.

[0074] Since optimizing a sorting plan may not necessarily pass logical function verification, if the optimized sorting plan fails to pass logical function verification, it cannot complete the package sorting and does not meet the sorting requirements. Therefore, it is meaningless to perform simulation performance verification on the optimized sorting plan.

[0075] To avoid performing useless simulation verification work and to avoid wasting resources, in some embodiments, when performing logical function verification and simulation performance verification on the optimized sorting plan, upon obtaining the target verification result, the optimized sorting plan is first logically verified, and then, based on the result of the logical function verification, it is determined whether to perform simulation performance verification.

[0076] After performing logical function verification on the optimized sorting plan and obtaining the first verification result, if the first verification result indicates that the optimized sorting plan has passed the logical function verification, then performing simulation performance verification on the optimized sorting plan based on the target simulation model to obtain the second verification result. Subsequently, based on the first and second verification results, the target verification result is generated. At this point, the target verification result includes both the first and second verification results.

[0077] Among them, the target simulation model is the simulation model corresponding to the optimized sorting plan, that is, the target simulation model is the simulation model of the target transfer site.

[0078] The first verification result indicates whether the optimized sorting plan has passed the logical function verification, that is, whether the optimized sorting plan can complete the sorting of packages. The second verification result includes the performance indicators of the optimized sorting plan, which indicate the sorting effect of the optimized sorting plan.

[0079] In other words, the first verification result may also indicate that the optimized sorting plan has failed the logical function verification, meaning that the optimized sorting plan cannot complete the sorting of packages and does not meet the sorting requirements of the packages.

[0080] If the first verification result indicates that the optimized sorting plan has failed the logical function verification, then a target verification result is generated based on the first verification result. In this case, the target verification result includes the first verification result.

[0081] In this way, simulation performance verification is performed only when the optimized sorting plan passes the logical function verification. If the optimized sorting plan fails the logical function verification, simulation performance verification is not performed. This avoids unnecessary simulation performance verification and effectively reduces resource waste.

[0082] In order to accurately determine whether the optimized sorting plan can complete the package sorting, in some embodiments, the optimized sorting plan is logically functionally verified. When the first verification result is obtained, relevant information on the package sorting requirements can be obtained first, and then the optimized sorting plan can be judged based on the relevant package sorting requirements information, i.e. whether it passes the logical function verification.

[0083] Parcel sorting requirements include compartment requirements, constraint requirements, flow requirements, labeling requirements, and package creation requirements.

[0084] The system acquires the packaging rules and analyzes the grid and tag information in the initial sorting plan. It then determines whether the optimized sorting plan conforms to the packaging rules and constraints, and whether it lacks grid and tag information, thus obtaining the first verification result. Grid information includes grid flow direction and grid type.

[0085] In addition, if the optimized sorting plan complies with the packaging rules and constraints, and the optimized sorting plan does not lack compartment information and tag information, the first verification result indicates that the optimized sorting plan has passed the logical function verification.

[0086] Correspondingly, if the optimized sorting plan does not comply with the packaging rules or constraints, or if the optimized sorting plan is missing compartment information or package tag information, the first verification result indicates that the optimized sorting plan has failed the logical function verification.

[0087] In other words, if the optimized sorting plan passes the logical function verification, the verification is recorded as successful; if the optimized sorting plan fails the logical function verification, the verification is recorded as unsuccessful.

[0088] Packing tag information includes all packing tags required for optimizing the sorting plan. For information on compartment information and packing tags, please refer to the above content.

[0089] Before determining whether the optimized sorting plan complies with the packaging rules and constraints, and whether the optimized sorting plan is missing any compartment information or tag information, it is necessary to first obtain the packaging rules, constraints, compartment information, and tag information.

[0090] The constraints can be user-inputted or determined by the system based on actual operating conditions.

[0091] Specifically, the system calls a third-party interface to obtain JSON messages containing the packaging rules for small parcels at each transit site, and stores them as files to obtain the required packaging rules.

[0092] In addition, the grid information includes the flow direction and grid type of each grid as specified in the initial sorting plan, and the tag information includes the tag of each grid as specified in the initial sorting plan.

[0093] When determining whether the optimized sorting plan is missing grid information, the grid information in the optimized sorting plan can be statistically analyzed to obtain the target grid information. The target grid information is then compared with the grid information in the initial sorting plan. If they are consistent, the optimized sorting plan is determined to be free of grid information. If the target grid information is missing at least one item of the grid information in the initial sorting plan, the optimized sorting plan is determined to be missing grid information.

[0094] When determining whether an optimized sorting plan is missing label information, the label information in the optimized sorting plan can be statistically analyzed to obtain the target label information. The target label information is then compared with the label information in the initial sorting plan. If they match, the optimized sorting plan is determined to be free of label information. If the target label information is missing at least one item from the label information in the initial sorting plan, the optimized sorting plan is determined to be missing label information.

[0095] In this embodiment, since the packaging rules, constraints, compartment information, and tag information can characterize the parcel sorting requirements, including compartment requirements, constraint requirements, flow requirements, tag requirements, and packaging requirements, by checking whether the optimized sorting plan meets the packaging rules and constraints, and whether the optimized sorting plan is missing compartment information and tag information, it is possible to accurately determine whether the optimized sorting plan has passed the logical function verification, thereby accurately determining whether the optimized sorting plan can meet the sorting requirements.

[0096] To achieve simulation performance verification, in some embodiments, the simulation performance of the optimized sorting plan is verified based on the target simulation model. When the second verification result is obtained, the target simulation model can be used to perform simulated sorting in combination with small package data, package creation rules and optimized sorting plan to obtain target simulation sorting data. Based on the target simulation sorting index, the target simulation sorting index is calculated, and thus the second verification result is generated based on the target simulation sorting index.

[0097] In conjunction with the above description of small parcel data, this data includes the scanning order and parcel information of the small parcels. Additionally, the second verification result includes the target simulation sorting index, which is the sorting index used during simulated sorting when the sorting plan is optimized.

[0098] Specifically, the small parcel data refers to the data on small parcels involved in the target shifts at the target transit hub.

[0099] The package information in the small package data is fed into the target simulation model along with the optimized sorting plan and packaging rules, according to the scanning order in the small package data, which is the actual scanning order. The model simulates the sorting process of small packages and records the sorting data of small packages passing through each node, including flow direction, scanning time, bag placement time, bag placement slot, and tying time, to obtain the target simulation sorting data.

[0100] In addition, sorting metrics include total sorting time, peak capacity, sorting machine return rate, parcel-to-parcel ratio, number of unloaded items, number of unloaded items, and number of extremely small parcels (the number of bundled parcels less than n small parcels).

[0101] One of the small parcels will fall into the bag under the corresponding compartment after being sorted by the sorting machine. When the bag is full or meets the conditions for tying, the bag will be packed. The parcel-to-bag ratio is the ratio of the number of parcels that have fallen into the compartment to the number of parcels that have been packed.

[0102] In this embodiment, based on the target simulation model of the target transfer area corresponding to the optimized sorting plan, combined with the scanning order and package information of small packages in the small package data, the package creation rules and the optimized sorting plan, simulated sorting is performed to obtain target simulated sorting data. Based on the target simulated sorting data, the target simulated sorting result is calculated and a second verification result is generated, which can realize the targeted simulation performance verification of the optimized sorting plan and obtain sorting indicators that can accurately characterize the performance of the optimized sorting plan.

[0103] At this point, a target verification result is generated based on the first verification result and the second verification result. Based on the target verification result, a verification report of sorting indicators that can characterize whether the optimized sorting plan can meet the sorting requirements and the efficiency of the optimized sorting plan can be generated. This facilitates understanding whether the optimized sorting plan can meet the sorting requirements and the efficiency of the optimized sorting plan, thereby realizing the testing of the optimization effect of the test piece and determining whether a better optimized sorting plan can be obtained through the test piece.

[0104] To understand whether the optimized sorting plan has been optimized, the direction of the optimized sorting plan, and the optimization effect of the test piece on the initial sorting plan, in some embodiments, the optimized sorting plan is simulated and its performance is verified based on the target simulation model. When the second verification result is obtained, the initial sorting plan is also simulated and its performance is verified to determine the sorting index of the initial sorting plan.

[0105] Based on the target simulation model, combined with small package data, package creation rules and initial sorting plan, simulated sorting is performed to obtain initial simulated sorting data. Then, based on the initial simulated sorting data, initial simulated sorting indicators are calculated. Finally, the initial simulated sorting indicators are added to the second verification results.

[0106] At this point, the second verification result includes the target simulation sorting index and the initial simulation sorting index. Among them, the initial simulation sorting index is the sorting index when the initial sorting plan is simulated.

[0107] The package information in the small package data is fed into the target simulation model along with the initial sorting plan and packaging rules, according to the scanning order in the small package data, which is the actual scanning order. The sorting process of small packages is simulated, and the sorting data of small packages passing through each node is recorded, including flow direction, scanning time, bag placement time, bag placement slot, and tying time, to obtain the initial simulation sorting data.

[0108] In this way, based on the target simulation sorting index and the initial simulation sorting index contained in the second verification result in the verification report, the performance difference between the optimized sorting plan and the initial sorting plan can be fully understood.

[0109] Furthermore, in order to clearly demonstrate the performance difference between the optimized sorting plan and the initial sorting plan, and to facilitate understanding of the optimization direction of the optimized sorting plan, in some embodiments, the optimized sorting plan is simulated and its performance is verified based on the target simulation model. When obtaining the second verification result, the initial simulation sorting index and the target simulation sorting index can be compared to obtain the comparison result, and the comparison result is added to the second verification result.

[0110] At this point, the second verification result includes the initial simulation sorting index, the target simulation sorting index, and the comparison result between the initial simulation sorting index and the target simulation sorting index.

[0111] The total sorting time is not so important; it is expected to be similar to the actual sorting time.

[0112] Generally, higher capacity leads to better sorting efficiency. More returned parcels result in longer conveyor belt usage time, potentially preventing new parcels from reaching the sorting machine and reducing capacity. A higher parcel-to-ticket ratio indicates fewer bundled parcels, effectively reducing the pressure on manual bundling and unpacking. A higher volume of unloaded parcels means more parcels requiring secondary sorting, reducing sorting capacity. A smaller volume of unloaded parcels results in fewer leftovers, fewer unsorted parcels within the specified time, and increased capacity. Fewer extremely small parcels mean lower energy consumption for unpacking at the next transfer point.

[0113] Therefore, the peak capacity of the optimized sorting plan is higher than that of the initial sorting plan, the average stable capacity of the optimized sorting plan is higher than that of the initial sorting plan, the return rate of the optimized sorting plan is lower than that of the initial sorting plan, the ticket-to-package ratio of the optimized sorting plan is higher than that of the initial sorting plan, the number of unloaded items in the optimized sorting plan is lower than that of the initial sorting plan, the amount of unloaded items in the optimized sorting plan is lower than that of the initial sorting plan, and / or, the number of extremely few packages in the optimized sorting plan is lower than that in the initial sorting plan.

[0114] The sorting metrics mentioned above may influence each other and cannot be judged from a single dimension. Usually, multiple dimensions / metrics are used to determine whether the optimized sorting metrics have been optimized relative to the initial sorting metrics.

[0115] In this embodiment, the comparison results are obtained by comparing the target simulated sorting index with the initial simulated sorting index, and the comparison results are added to the second verification results. The optimization effect of the optimized sorting plan relative to the initial sorting plan can be fully understood through the second verification results.

[0116] Based on the above introduction to small parcel data, it can be seen that small parcel data also includes actual bagging data of small parcels. Accordingly, the above initial simulation sorting data includes simulated bagging data.

[0117] In some embodiments, the grid distortion of each grid is determined based on actual bag-dropping data and simulated bag-dropping data. Then, the model distortion is determined based on the grid distortion. Subsequently, when generating the second verification result, the model distortion can be added to the second verification result. In this way, the verification report generated based on the target verification result also includes the model distortion, which is the distortion of the target simulation model.

[0118] Before obtaining the second verification result, based on the actual bag-dropping data, the actual number of bags dropped into each compartment is counted. Based on the simulated bag-dropping data, the simulated number of bags dropped into each compartment is counted. Then, for each compartment, the compartment distortion degree is determined based on the ratio of the difference between the simulated number of bags dropped into and the actual number of bags dropped into to the actual number of bags dropped into. The sum of the compartment distortion degrees of all compartments is determined as the model distortion degree.

[0119] At this point, the performance of the optimized simulation plan is verified based on the target simulation plan. When obtaining the second verification result, the model distortion is also added to the second verification result. The verification report generated based on the second verification result includes the model distortion.

[0120] Specifically, for each compartment, after determining the ratio of the difference between the simulated number of packages dropped into the bag and the number of packages dropped into the bag in time to the actual number of packages dropped into the bag, the product of this ratio and a preset weight is used as the compartment distortion degree.

[0121] There is a corresponding relationship between the preset weights and the compartments. Generally, the preset weight for any compartment is the ratio of the actual number of bags placed in that compartment to the total number of items, where the total number of items is the sum of the actual number of bags placed in all compartments.

[0122] In this way, based on the difference between the actual bag-dropping data and the simulated bag-dropping data for each compartment, and the ratio of this difference to the actual number of bags dropped, the compartment distortion degree for each compartment is determined. The sum of the compartment distortion degrees for all compartments is then used to determine the model distortion degree, resulting in a relatively accurate model distortion degree. This model distortion degree is then added to the second verification result. A verification report is generated based on the second verification result, allowing the model simulation accuracy to serve as a reference for the second verification result, facilitating understanding of the reliability of the second verification result for relevant personnel.

[0123] In some cases, the target simulation model has poor reliability. The results of simulation performance verification based on a poorly reliable target simulation model are not meaningful and cannot accurately represent the effectiveness of optimizing the sorting plan. To avoid unnecessary simulation performance verification and ensure its accuracy, in some embodiments, a second verification result is determined based on the model distortion.

[0124] After determining the grid distortion of all grids as the model distortion, the second verification result is determined based on the model distortion and the preset distortion threshold.

[0125] Specifically, if the model distortion is greater than the preset distortion threshold, the operation of verifying the simulation performance of the optimized sorting plan based on the target simulation model and obtaining the second verification result will not be performed, and the model distortion will be used as the second verification result; if the model distortion is not greater than the preset distortion threshold, the operation of verifying the simulation performance of the optimized sorting plan based on the target simulation model and obtaining the second verification result will be performed, and the model distortion will be added to the second verification result.

[0126] Since the bag placement has a certain degree of randomness, the simulation results may not be completely consistent with the real data. A preset distortion threshold is defined. When the calculated model distortion is lower than the preset distortion threshold, the target simulation model is considered reliable. Conversely, when the calculated model distortion is higher than the preset distortion threshold, the target simulation model is considered unreliable.

[0127] When the target simulation model is reliable, the operation of verifying the simulation performance of the optimized sorting plan based on the target simulation model is performed. At this time, the second verification result includes model distortion and target simulation sorting index, etc.

[0128] When the target simulation model is unreliable, the operation of verifying the simulation effectiveness of the optimized simulation plan based on the target simulation model is not performed. In this case, the second verification result only includes the model distortion.

[0129] When the distortion of the target simulation model exceeds the preset distortion threshold, the target simulation model can be recorded as needing optimization.

[0130] The preset distortion threshold can be adjusted based on the number of packages and sorting time.

[0131] Generally, for any given shift, the fewer the number of packages sorted and the shorter the sorting time, the greater the potential for random errors in the simulation. Therefore, when the number of packages sorted in a shift is small and / or the sorting time is short, the preset distortion threshold should be increased; conversely, when the number of packages sorted in a shift is large and / or the sorting time is long, the preset distortion threshold should be decreased.

[0132] In this embodiment, the simulation performance verification operation based on the target simulation model is performed only when the model distortion is below the preset simulation degree threshold, assuming the target simulation model is reliable. This effectively ensures the reliability of the target simulation sorting indicators obtained from the performance simulation. When the model distortion is above the preset simulation degree threshold, i.e., when the target simulation model is unreliable, the simulation performance verification operation is not performed, which reduces unnecessary simulation performance verification and effectively reduces resource waste.

[0133] Due to the large number of transit hubs, with multiple shifts in each hub and at least one sorting device in each hub, users may need to simultaneously observe the sorting effects of optimized sorting plans for multiple sorting devices across multiple shifts in multiple transit hubs. To facilitate simultaneous observation of the sorting effects of optimized sorting plans for different sorting devices across different shifts in all transit hubs, in some embodiments, when generating and outputting a verification report based on the target verification results, it is necessary to check whether the verification of all required optimized sorting plans has been completed. After completing the verification of all required optimized sorting plans, a verification report is generated and output based on the target verification results of all required optimized sorting plans.

[0134] Specifically, if the target verification results of the optimized sorting plan for each target sorting device in each target shift of each target transfer area are determined, a verification report is generated and output based on all target verification results.

[0135] Accordingly, if the target verification results of the optimized sorting plan for each target sorting equipment in each target shift of each target transfer area are not determined, the optimized sorting plan that has not been verified is verified. After the verification of all optimized sorting plans is completed, a verification report is generated and output based on all target verification results.

[0136] Thus, in this embodiment, after verifying all the optimized sorting plans that need to be verified, a verification report is generated and output based on all the target verification results. This achieves the goal of simultaneously observing the sorting effect of the optimized sorting plans of multiple sorting equipment in multiple shifts at multiple transfer stations, thus avoiding omissions.

[0137] This application also provides a sorting plan generation system, which includes a data processing module, a test execution module, a result verification module, and a report generation module.

[0138] Taking this sorting plan generation system as an example, the sorting plan generation process may include, for example, the process shown in Figure 2.

[0139] The daily parcel data from all transit hubs across the network is massive and diverse, including small parcels, large parcels, irregularly shaped parcels, and chilled parcels. The data processing module is used to collect, extract, and process small parcel data from this daily data. Specifically, the module filters and selects relevant data for small parcels from each transit hub's BDP (Business Data Point) table, including data from each parcel's scanning, unpacking, loading, and bagging processes, completing the extraction and storage of small parcel data.

[0140] The data processing module is used to call the interface of a third-party system to obtain the original sorting plan (i.e., the initial sorting plan) JSON message of each site, realize the query of small item sorting plan, and store it as a file.

[0141] The data processing module is used to call third-party system interfaces to obtain JSON messages of small parcel creation rules for each site, realize the query of small parcel summary rules, and store them as files.

[0142] The data processing module is also used to summarize the data it acquires, that is, to summarize the data and obtain the relationship between the straight grid, mixed grid and return grid and the package set, flow code, etc.

[0143] The data processing module is also used to aggregate parcel information from various transit sites, extract a list of shift IDs and corresponding sorting time periods by transit site, generate site shift information files, and complete the extraction of site shift information.

[0144] Next, the test execution module is used to traverse the site shift information (file), add constraint options / fields according to the site shift to construct the request message body, and send the request constructed by the request message body to the test device via HTTP communication. That is, send the request to the test device. After the test device runs, it calls the small item sorting plan optimization service to optimize and obtain the optimized (post) sorting plan.

[0145] Next is the result verification module, which is used to verify the optimization results, i.e., the optimized sorting plan.

[0146] The result verification module is used to perform logical and functional verification on the optimized sorting plan. Specifically, it determines whether the grid information is abnormal, whether the constraints are met, whether the flow direction is missing, whether the package label is missing, and whether the direct sorting grid, mixed sorting grid, and / or return grid are missing. If it fails, the test result is recorded as a failure, and the simulation of the next optimized sorting plan begins.

[0147] The results verification module also inputs the package information from the small package data into the digital twin simulation model (target simulation model) according to the actual scanning order and the initial sorting plan and packaging rules. This simulates the small package sorting process and records the sorting data (including flow direction, scanning time, bag placement time, bag placement slot, and tying time) at each node. The module compares the simulated number of packages placed per slot per unit time (e.g., per minute) with the actual number of packages placed per slot. Dividing this difference by the actual number of packages placed per slot, and then multiplying by, for example, the weight of the number of packages in that slot, the distortion of each slot is calculated. The model distortion is the sum of the distortions of each slot. The weight is the number of packages placed per slot / total number of packages. Generally, slots with more packages placed per slot have a greater weight than slots with fewer packages placed per slot. The simulated number of packages placed per slot per unit time represents the initial sorting plan's actual package placement performance, while the actual number of packages placed per slot per unit time represents the initial sorting plan's actual package placement performance.

[0148] Because bag placement has a certain degree of randomness, simulation results cannot be 100% consistent with real data. The result verification module is also used to determine the reliability of the model based on its distortion. Specifically, a preset distortion threshold 'a' is defined. When the calculated model distortion is lower than threshold 'a', the simulation model is considered reliable. The threshold 'a' can be adjusted according to the number of packages and sorting time. If the distortion is higher than the threshold, the simulation model needs optimization, the test results are recorded as the second verification result, and the model proceeds to the next optimized sorting plan test.

[0149] The results verification module is also used to input package data into the simulation model according to the actual scanning order and the optimized sorting plan and packaging rules, record the sorting data, and obtain the simulated package placement performance of the optimized sorting plan. Based on the simulated package placement performance of the optimized sorting plan and the simulated sorting data of the initial sorting plan, i.e. the simulated package placement performance of the initial sorting plan, the indicators are calculated respectively, including: total sorting time, peak capacity, sorting machine return rate, ticket-to-package ratio, number of unloaded items, number of unloaded items, number of packages with fewer than n items, etc., and the advantages and disadvantages of each indicator are compared, i.e., the sorting plan performance before and after optimization is compared.

[0150] Finally, the report generation module is used to obtain the result information, indicator information, and software defect information of the above-mentioned functional verification module, store the target verification results, and generate a verification report.

[0151] In addition, this sorting plan optimizes the continuous integration module (continuous integration is a name; this module automatically pushes reports to relevant personnel after testing is completed. It can be set to automatically execute test tasks and push test reports automatically after completion, for example, using the commercially available continuous integration tool Jenkins) to trigger emails, enterprise communication assistants, WeChat Work, and other methods to send reports to simulation personnel.

[0152] Exemplary device

[0153] As shown in Figure 3, this application embodiment also provides a sorting plan generation device, including an acquisition module 301, a verification module 302, a reporting module 303, and a plan generation module 304.

[0154] The acquisition module 301 is used to acquire the optimized sorting plan of the target sorting equipment in the target shift of the target transfer station; the verification module 302 is used to perform logical function verification and simulation verification on the optimized sorting plan; the plan generation module 304 is used to obtain a new sorting plan based on the target verification results; and the report module 303 is used to generate and output a verification report based on the target verification results.

[0155] The sorting plan generation device provided in this embodiment belongs to the same concept as the sorting plan generation method provided in the above embodiments of this application. It can execute the method provided in any of the above embodiments of this application and has the corresponding functional modules and beneficial effects of the method. Technical details not described in detail in this embodiment can be found in the specific processing content of the sorting plan generation method provided in the above embodiments of this application, and will not be repeated here.

[0156] The functions implemented by the acquisition module 301, verification module 302, reporting module 303 and plan generation module 304 can be implemented by the same or different processors calling software, and this application embodiment does not limit this.

[0157] Exemplary electronic devices

[0158] Another embodiment of this application also proposes an electronic device, as shown in FIG4, which includes a memory 400 and a processor 410.

[0159] The memory 400 is connected to the processor 410 and is used to store programs; the processor 410 is used to implement the sorting plan generation method disclosed in any of the above embodiments by running the programs stored in the memory 400.

[0160] Specifically, the electronic device may also include: a bus, a communication interface 420, an input device 430, and an output device 440.

[0161] The processor 410, memory 400, communication interface 420, input device 430, and output device 440 are interconnected via a bus. Among them:

[0162] A bus can include a pathway for transmitting information between various components of a computer system.

[0163] The processor 410 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present application. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0164] Processor 410 may include a main processor, as well as a baseband chip, modem, etc.

[0165] The memory 400 stores a program for executing the technical solution of this application, and may also store an operating system and other critical business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory 400 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0166] Input device 430 may include a device for receiving user input data and information, such as a keyboard, mouse, camera, scanner, light pen, voice input device, touch screen, pedometer, or gravity sensor.

[0167] Output device 440 may include devices that allow information to be output to a user, such as a display screen, printer, speaker, etc.

[0168] The communication interface 420 may include a device that uses any transceiver to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0169] The processor 410 executes the program stored in the memory 400 and calls other devices, which can be used to implement any of the steps of the sorting plan generation method provided in the above embodiments of this application.

[0170] Those skilled in the art will understand that the structure shown in Figure 4 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0171] This application also proposes a chip, which includes a processor and a data interface. The processor reads and runs a program stored in a memory through the data interface to execute the sorting plan generation method described in any of the above embodiments. For details of the processing and its beneficial effects, please refer to the embodiments of the sorting plan generation method described above.

[0172] In addition to the methods and apparatus described above, embodiments of this application provide a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps of the sorting plan generation method according to various embodiments of this application as described in the "Exemplary Methods" section of this specification.

[0173] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0174] Furthermore, embodiments of this application also propose a storage medium storing a computer program that is executed by a processor in the sorting plan generation method according to various embodiments of this application as described in the "Exemplary Methods" section above.

[0175] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0176] The block diagrams of devices, apparatuses, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0177] It should also be noted that in the apparatus, device, and method of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of the present invention.

[0178] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0179] It should be understood that the qualifying terms "first", "second", "third", "fourth", "fifth" and "sixth" used in the description of the embodiments of the present invention are only used to more clearly illustrate the technical solutions and are not intended to limit the scope of protection of the present invention.

[0180] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A sorting plan generation method characterized by comprising: The method comprises: obtaining an optimized sorting plan of a target sorting device in a target shift of a target transfer station; performing logical function verification and simulation performance verification on the optimized sorting plan to obtain a target verification result; obtaining a new sorting plan based on the target verification result.

2. The sorting plan generation method according to claim 1, characterized by, The method comprises: obtaining an optimized sorting plan of a target sorting device in a target transfer station; obtaining an initial sorting plan of the target sorting device in the target shift of the target transfer station; constructing a request message body based on the target transfer station, the target shift, and the target sorting device, combining constraint conditions, and generating a sorting plan optimization request, wherein the sorting plan optimization request comprises the request message body; 3. The sorting plan generation method according to claim 2, characterized by, optimizing the initial sorting plan based on the sorting plan optimization request to obtain the optimized sorting plan. The method comprises: performing logical function verification on the optimized sorting plan to obtain a first verification result; if the first verification result indicates that the optimized sorting plan passes the logical function verification, performing simulation performance verification on the optimized sorting plan based on a target simulation model to obtain a second verification result, wherein the target simulation model is a simulation model of the target transfer station; 4. The sorting plan generation method according to claim 3, characterized by, generating the target verification result based on the first verification result and the second verification result, wherein the target verification result comprises the first verification result and the second verification result. The method further comprises:

5. The sorting plan generation method according to claim 3, characterized by, if the first verification result indicates that the optimized sorting plan fails the logical function verification, generating the target verification result based on the first verification result. The method comprises: obtaining a build package rule and counting bin information and package label information in the initial sorting plan, wherein the bin information comprises bin flow direction and bin type; determining whether the optimized sorting plan conforms to the build package rule and the constraint condition, and whether the optimized sorting plan is missing the bin information and the package label information to obtain the first verification result; 6. The sorting plan generation method according to claim 3, characterized by, wherein the optimized sorting plan conforms to the build package rule and the constraint condition, and the optimized sorting plan is not missing the bin information and the package label information, the first verification result indicates that the optimized sorting plan passes the logical function verification. The method comprises: based on the target simulation model, combining small package data, the build package rule, and the optimized sorting plan to perform simulation sorting to obtain target simulation sorting data, wherein the small package data comprises small package scanning order and package information; based on the target simulation sorting data, calculating the target simulation sorting index; Generate a second verification result based on the target simulation sorting index, wherein the second verification result includes the target simulation sorting index.

7. The sorting plan generation method according to claim 6, characterized in that, The simulation performance verification of the optimization sorting plan based on the target simulation model further includes: Based on the target simulation model, combine the small package data, the package building rule, and the initial sorting plan to perform simulation sorting and obtain initial simulation sorting data; Based on the initial simulation sorting data, calculate the initial simulation sorting index; Add the initial simulation sorting index to the second verification result.

8. The sorting plan generation method according to claim 7, characterized by, The simulation performance verification of the optimization sorting plan based on the target simulation model further includes: Compare the initial simulation sorting index with the target simulation sorting index to obtain a comparison result; Add the comparison result to the second verification result.

9. The sorting plan generation method according to claim 7, characterized by, The small package data includes actual package dropping data of small packages, the initial simulation sorting data includes simulation dropping data, the verification report includes model distortion, and the model distortion is the distortion of the target simulation model. Before the simulation performance verification of the optimization sorting plan based on the target simulation model to obtain the second verification result, the method further includes: Based on the actual dropping data, count the actual dropping package quantity of each bin; Based on the simulation dropping data, count the simulation dropping package quantity of each bin; For each bin, determine the bin distortion based on the difference between the simulation dropping package quantity and the actual dropping package quantity, and the ratio of the simulation dropping package quantity to the actual dropping package quantity; Determine the sum of the bin distortions of all bins as the model distortion; The simulation performance verification of the optimization sorting plan based on the target simulation model to obtain the second verification results further includes adding the model distortion to the second verification result.

10. The sorting plan generation method according to claim 9, characterized by, After determining the sum of the bin distortions of all bins as the model distortion, the method further includes: If the model distortion is greater than a preset distortion threshold, do not perform the simulation performance verification of the optimization sorting plan based on the target simulation model to obtain the second result, and use the model distortion as the second verification result; If the model distortion is not greater than the preset distortion threshold, perform the simulation performance verification of the optimization sorting plan based on the target simulation model to obtain the result, and add the model distortion to the second verification result.

11. The sorting plan generation method according to any one of claims 1 to 10, characterized by, Further includes: Generate a verification report based on the target verification result and output it.

12. The sorting plan generation method according to claim 11, characterized by, The generation of the verification report based on the target verification result and the output thereof include: If the target verification result of the optimization sorting plan of each target sorting device in each target shift of each target transfer field is determined, generate the verification report based on all the target verification results and output it.

13. An electronic device, comprising: Include a memory and a processor; The memory is connected with the processor and is used for storing programs; The processor is configured to implement the sorting plan generation method according to any one of claims 1-12 by running a program in the memory.

14. A storage medium, characterized by The storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the sorting plan generation method according to any one of claims 1-12.

15. A computer program product, characterised in that, The computer program product comprises computer program instructions, which, when executed by a processor, cause the processor to perform the sorting plan generation method according to any one of claims 1-12.

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