Delivery task allocation method and device, computer device and storage medium

Abstract

A delivery task allocation method and device, a computer device and a storage medium, the method comprising: obtaining specific express information of each unit area in a current transfer station and network point information of a network point covered by the current transfer station; constructing a static area division model according to the specific express information and the network point information, and determining two or more static areas in a covered area of the current transfer station and the number of delivery personnel corresponding to each static area based on the static area division model, with the goal of task balance and minimizing the total number of delivery personnel; constructing a task allocation model according to the static areas and the corresponding number of delivery personnel, and determining a delivery task allocation plan for the unit areas in each static area to belong to a delivery task based on the task allocation model, with the goal of task balance; and determining the corresponding delivery personnel for the delivery task according to the delivery task allocation plan. The above method not only ensures the minimum number of delivery personnel, but also ensures the task balance between each delivery personnel.

Description

Technical Field

[0001] The present application relates to the field of logistics technology, and in particular to a delivery task allocation method, apparatus, computer equipment, and storage medium. Background Art

[0002] In the logistics delivery process, express parcels are typically distributed from transit stations to various city-wide distribution centers (the smallest distribution center), and then delivered from these distribution centers to the recipients. However, for special parcels, such as heavy items, delivery becomes difficult due to the limitations of delivery vehicles. Therefore, for these special parcels, direct delivery from transit stations to a unit area (the smallest delivery area) is often chosen.

[0003] Usually, each transfer station has a relatively large coverage area. If you choose to deliver directly from the transfer station to the unit area, you must consider the number of delivery personnel and the task balance among the delivery personnel. It is particularly important to reasonably allocate the delivery tasks. Summary of the Invention

[0004] Based on this, it is necessary to provide a delivery task allocation method, device, computer equipment and storage medium that can ensure a reasonable number of delivery personnel and a balanced task distribution among delivery personnel in order to address the above technical problems.

[0005] A method for allocating delivery tasks, the method comprising:

[0006] Obtain specific express delivery information for each unit area within the current transfer station and network information of the network points covered by the current transfer station;

[0007] Constructing a static area division model based on the specific express delivery information and the network point information, and determining two or more static areas within the current transfer station coverage area and the number of delivery personnel corresponding to each static area based on the static area division model with the goal of balancing tasks and minimizing the total number of delivery personnel;

[0008] Constructing a task allocation model based on the static areas and the corresponding number of delivery personnel, and determining a delivery task allocation plan for assigning delivery tasks to unit areas within each static area based on the task allocation model with a goal of task balance;

[0009] Determine corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0010] In one embodiment, the static area division model includes a total number of delivery personnel determination stage model and an area division stage model;

[0011] The goal of the model in the stage of determining the total number of delivery personnel is to minimize the total number of delivery personnel, and the goal of the model in the stage of area division is to balance tasks.

[0012] In one embodiment, the constraints of the model in the stage of determining the total number of delivery personnel include: static area division constraints, static area population constraints, and inter-network enclave constraints; the constraints of the model in the stage of area division include: static area division constraints, static area population constraints, inter-network enclave constraints, total number of delivery personnel constraints, and task balancing auxiliary constraints.

[0013] In one embodiment, when the number of unit areas contained in the static area does not exceed a preset threshold, the task allocation model includes a task packaging stage model and a post-processing model; the delivery task packaging stage model assigns delivery tasks to unit areas with the goal of task balance; the delivery task includes multiple unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned of the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0014] In one embodiment, when the number of unit areas contained in the static area exceeds the preset threshold, the task allocation model includes a candidate area division stage model, a task packaging stage model and a post-processing model; the candidate area division stage model divides the static area into two or more candidate areas with the goal of minimizing the sum of distances between the unit areas in the candidate area; any of the candidate areas contains more than two unit areas; the task packaging stage model assigns delivery tasks to each candidate area with the goal of task balance; the delivery task includes more than two unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned of the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0015] In one embodiment, the constraints of the candidate area division stage model include: candidate area division constraints, candidate area quantity constraints, candidate area piece quantity constraints and candidate area weight constraints; the constraints of the task packaging stage model include: packaging constraints, total number of delivery personnel constraints, task piece quantity constraints, task weight constraints, delivery task area range constraints, enclave constraints between unit areas, and task balance auxiliary constraints; the constraints of the post-processing model include: task attribution uniqueness constraints, task attribution distance constraints and task balance auxiliary constraints.

[0016] In one embodiment, the goal of task balancing includes minimizing the average deviation between the task value assigned to each delivery person and the average task value per person.

[0017] A delivery task allocation device, comprising:

[0018] An information acquisition module is used to obtain specific express delivery information of each unit area in the current transfer station and the network information of the network points covered by the current transfer station;

[0019] A static area division module is configured to construct a static area division model based on the specific express delivery information and the outlet information, and based on the static area division model, determine two or more static areas within the current transfer yard coverage area, and the number of delivery personnel corresponding to each static area, with the goal of balancing tasks and minimizing the total number of delivery personnel;

[0020] A task allocation model is used to construct a task allocation model based on the static areas and the corresponding number of delivery personnel, and based on the task allocation model, determine a delivery task allocation plan for assigning unit areas within each static area to delivery tasks with a goal of task balance;

[0021] The task allocation module is used to determine the corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0022] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0023] Obtain specific express delivery information for each unit area within the current transfer station and network information of the network points covered by the current transfer station;

[0024] Constructing a static area division model based on the specific express delivery information and the network point information, and determining two or more static areas within the current transfer station coverage area and the number of delivery personnel corresponding to each static area based on the static area division model with the goal of balancing tasks and minimizing the total number of delivery personnel;

[0025] Constructing a task allocation model based on the static areas and the corresponding number of delivery personnel, and determining a delivery task allocation plan for assigning delivery tasks to unit areas within each static area based on the task allocation model with a goal of task balance;

[0026] Determine corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0027] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0028] Obtain specific express delivery information for each unit area within the current transfer station and network information of the network points covered by the current transfer station;

[0029] Constructing a static area division model based on the specific express delivery information and the network point information, and determining two or more static areas within the current transfer station coverage area and the number of delivery personnel corresponding to each static area based on the static area division model with the goal of balancing tasks and minimizing the total number of delivery personnel;

[0030] Constructing a task allocation model based on the static areas and the corresponding number of delivery personnel, and determining a delivery task allocation plan for assigning delivery tasks to unit areas within each static area based on the task allocation model with a goal of task balance;

[0031] Determine corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0032] The above-mentioned delivery task method, device, computer equipment and storage medium first obtain the specific express information of each unit area in the current transfer yard, as well as the information of the outlets covered by the transfer yard, and construct a static area division model based on the specific express information and outlet information. With the goal of minimizing the total number of delivery personnel and balancing tasks, the static area division model is used to divide the area covered by the transfer yard into two or more static areas, as well as the number of delivery personnel assigned to each static area. Then, a task allocation model is constructed based on the number of delivery personnel corresponding to the static areas. With the goal of task balance, the task allocation model is used to allocate tasks to each static area, thereby obtaining a delivery task allocation plan for the unit area belonging to the delivery task, and finally, the corresponding delivery personnel are determined for the delivery task according to the delivery task allocation plan. The above method divides task allocation into two stages. First, the large area covered by the transfer station is divided into multiple static areas with the goal of minimizing the number of delivery personnel, and the number of delivery personnel assigned to each static area is determined. Then, delivery tasks are allocated in the static areas with the goal of task balance. This ensures that the number of delivery personnel is minimized and the tasks are balanced among the delivery personnel, thereby reducing the overall management difficulty of the transfer station. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flowchart of a method for allocating delivery tasks in one embodiment is shown;

[0034] Figure 2 A flowchart of a method for allocating delivery tasks in a specific embodiment is shown;

[0035] Figure 3 It is a structural block diagram of a delivery task allocation device in one embodiment;

[0036] Figure 4FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0038] In one embodiment, Figure 1 As shown, a method for allocating delivery tasks is provided. This embodiment uses the method applied to a terminal as an example. It is understood that the method can also be applied to a server, or to a system including a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes steps S110 to S140.

[0039] Step S110, obtaining specific express parcel information of each unit area in the current transfer yard and network point information of the network points covered by the current transfer yard.

[0040] A transit point (station) is a distribution node in the network, whose primary function is to collect, distribute, and transship express parcels. These points are also known as distribution points or centers. From a network perspective, a transit point is also a network node. A transit point is a crucial node for sorting and distributing express parcels. Its operating model is primarily characterized by the fact that it is not an organizational unit engaged in the production of specific goods. Instead, it primarily concentrates, exchanges, and transships parcels collected from other points, enabling the flow of parcels from decentralized to centralized and then decentralized throughout the network. In practice, parcels from other points connected to the transit point are gathered at the transit point during a specific period of time and then exchanged. The current transit point represents the current transit point where delivery tasks are assigned.

[0041] A network point is a distribution center under a transfer station. A transfer station covers at least one network point. In one embodiment, a network point is a distribution center at the lowest level. In one embodiment, the network point information of the network points currently covered by the transfer station includes the number of network points within the current transfer station's coverage area, and each network point corresponds to a coverage area.

[0042] A specific express parcel refers to an express parcel that needs to be directly assigned a delivery task at the current transfer station; in one embodiment, in the delivery link of the logistics scenario, express parcels are usually distributed from the transfer station to various outlets in the city (the smallest level distribution center), and then delivered from each outlet to the recipient user; and in some special cases, the express parcel will be delivered directly to the recipient user by the delivery personnel at the transfer station. These express parcels delivered directly from the transfer station by the delivery personnel to the recipient are the specific express parcels in this embodiment. In one embodiment, specific express parcels include express parcels with a weight greater than a threshold; in another embodiment, specific express parcels include express parcels with special time requirements. In other embodiments, specific express parcels can also be other express parcels that need to be delivered directly from the transfer station by the delivery personnel to the consignee.

[0043] Specific shipment information includes the attributes of the specific shipment. In one embodiment, the specific shipment information includes the total number of specific shipments, the unit area to which the recipient address of each specific shipment belongs, and so on. Furthermore, based on the recipient address information of each specific shipment, the number of specific shipments within each unit area can be determined.

[0044] In one embodiment, the specific express delivery information obtained for each unit area within the current transfer station is historical express delivery information, that is, the delivery tasks are divided (divided into unit areas) using the historical express delivery information of the current transfer station. Furthermore, in one embodiment, specific express delivery information within a preset historical time period is obtained, where the preset historical time period can be set according to actual conditions. For example, it can be set to obtain historical information of specific express deliveries within the past 7 days, the past 1 month, or the past 3 months, or it can be set to obtain historical information of specific express deliveries within the same month of the previous year (such as if the current time is November, historical information of specific express deliveries in November of the previous year is obtained), or it can also be set to obtain information on specific express deliveries within an average of one month within the past 12 months, etc. In another embodiment, the specific express delivery information obtained for each unit area within the current transfer station is information on specific express deliveries directly assigned within the current transfer station, and the delivery tasks are directly assigned using the information of specific express deliveries that need to be assigned.

[0045] Step S120, construct a static area division model based on specific express information and network information, and based on the static area division model, determine two or more static areas within the current transfer yard coverage area, as well as the number of delivery personnel corresponding to each static area, with the goal of task balance and minimization of the total number of delivery personnel.

[0046] The static zone division model divides the area covered by the current transfer site into two or more static zones. Each static zone is assigned a specific number of delivery personnel based on the number of parcels within its coverage area. Each static zone also includes at least one network area. Static zones are a virtual layer between transfer sites and unit areas, existing to facilitate transfer site management and subsequent task allocation.

[0047] When building a model, it is necessary to define the model's parameters, constraints, objectives, and outputs, among other information. In this embodiment, the parameters required for the static region segmentation model include specific package information and network point information. In one specific embodiment, the static region model can be constructed using a model solver.

[0048] A delivery task refers to a parcel that a delivery person needs to deliver. A delivery task may include multiple unit areas, with each specific parcel within each unit area belonging to one of the delivery tasks. Each delivery task corresponds to one delivery person. Assuming that delivery person A is assigned delivery task 1, which includes unit areas 1-10, all parcels within unit areas 1-10 will be delivered by delivery person A. Furthermore, the goal of task balancing is to ensure that the assigned delivery tasks are balanced for each delivery person. Furthermore, in one embodiment, task balancing includes balancing the task values ​​corresponding to the delivery tasks. Whether task balancing has been achieved can be determined by calculating the difference between the total value of the delivery tasks assigned to each delivery person and the per capita task value.

[0049] In one embodiment, the total task value corresponding to the delivery tasks assigned to each delivery person is calculated, the difference between the total task value assigned to each delivery person and the average task value per person is calculated, and the average of the absolute values ​​of all the differences is calculated. When the average of the absolute values ​​of the differences is small, it is determined that the tasks assigned to each delivery person are balanced. Furthermore, it can be set that when the average of the differences is less than a certain threshold, the tasks are determined to be balanced. The average task value per person can be determined based on the total task value and the total number of delivery persons; and the total task value is the sum of the values ​​of all specific express parcels. In one embodiment, the goal of task balance includes minimizing the average deviation between the delivery task value assigned to each delivery person and the average task value per person.

[0050] Furthermore, the calculation of the total task value requires consideration of specific delivery task information. In one embodiment, the number, weight, delivery distance, and unit value of specific parcels within each unit area of ​​the delivery task are obtained, and the value of each parcel is determined based on the number, weight, delivery distance, and unit value of each parcel. The total task value represents the sum of the values ​​of all parcels included in a delivery task for a delivery person. In other embodiments, the total task value can also be determined using other methods.

[0051] The goal of minimizing the total number of delivery personnel means that for all express parcels within the area covered by the current transit site, the total number of delivery personnel required is the least. In this embodiment, the two goals of task balance and minimization of delivery personnel are taken into account at the same time, and the area covered by the transit site is divided into two or more static areas, so that a more reasonable balance is achieved in the static area division and personnel allocation within the area covered by the current transit site. It can be understood that due to the constraints of the actual situation, there are certain constraints on the allocation of static areas and personnel, and these constraints can be determined according to the actual situation; for example, the upper limit on the total number of delivery personnel, the upper limit on the tasks assigned to each delivery personnel, and so on.

[0052] In a specific embodiment, after constructing a static area division model, the area covered by the current transfer place is divided into two or more static areas based on the static area division model, and the number of delivery personnel corresponding to each static area obtained by division is determined based on the static area division model. That is, the area covered by the current transfer place is divided into two or more static areas, and fixed delivery personnel are configured in each static area. In one embodiment, the static area output by the static area division model is the range covered by the static area, which can be represented by which unit areas are covered; for example, static area 1 covers unit areas 1 to 100.

[0053] It can be further understood that if the number of delivery personnel corresponding to a static area is greater than one, then it is necessary to subsequently evenly distribute delivery tasks to each delivery personnel in each static area.

[0054] Step S130 , constructing a task allocation model according to the static areas and the corresponding number of delivery personnel, and determining a delivery task allocation plan for assigning unit areas within each static area to delivery tasks based on the task allocation model with the goal of task balance.

[0055] The task allocation model is used to allocate unit areas within the static area to each delivery personnel. Similar to the static area division model, when constructing the task allocation model, it is necessary to define the parameters required by the model, the constraints of the model, the objectives of the model, the output of the model, and other information; among which, in this embodiment, the parameters required by the model include the static area and the corresponding number of delivery personnel; if the coverage range of the static area is known, the unit areas covered in the static area can be determined. The output of the task allocation model includes the delivery tasks belonging to the unit areas respectively, which is recorded as the delivery task allocation plan in this embodiment. In a specific embodiment, the process of constructing the task allocation model can be implemented by a model solver.

[0056] The goal of task allocation is task balance. This step is the same as the task balance in step S120 and will not be further elaborated here. Understandably, due to practical constraints, there are certain constraints on the allocation of static areas and personnel. These constraints can be determined based on actual conditions; for example, there is a limit on the number of tasks assigned to each delivery person, etc.

[0057] Step S140: determining a corresponding delivery person for the delivery task according to the delivery task allocation plan.

[0058] After obtaining the delivery task allocation plan, we can know the total number of express delivery personnel required and the delivery tasks belonging to each unit area within the coverage of the current transfer station; on this basis, we can assign specific delivery personnel to undertake the corresponding delivery tasks.

[0059] The above-mentioned delivery task method first obtains the specific express information of each unit area in the current transfer yard, as well as the information of the outlets covered by the transfer yard, and constructs a static area division model based on the specific express information and outlet information. With the goal of minimizing the total number of delivery personnel and balancing tasks, the static area division model is used to divide the area covered by the transfer yard into two or more static areas, as well as the number of delivery personnel assigned to each static area. Then, a task allocation model is constructed based on the number of delivery personnel corresponding to the static areas. With the goal of task balance, the task allocation model is used to allocate tasks to each static area, thereby obtaining a delivery task allocation plan for the unit area belonging to the delivery task, and finally, the corresponding delivery personnel are determined for the delivery task according to the delivery task allocation plan. The above method divides task allocation into two stages. First, the large area covered by the transfer station is divided into multiple static areas with the goal of minimizing the number of delivery personnel, and the number of delivery personnel assigned to each static area is determined. Then, delivery tasks are allocated in the static areas with the goal of task balance. This ensures that the number of delivery personnel is minimized and the tasks are balanced among the delivery personnel, thereby reducing the overall management difficulty of the transfer station.

[0060] Furthermore, in one embodiment, the static area division model includes a total number of dispatch personnel determination stage model and an area division stage model; the goal of the total number of dispatch personnel determination stage model is to minimize the total number of dispatch personnel, and the goal of the area division stage model is task balance.

[0061] In this embodiment, static area division is divided into two phases: a phase model for determining the total number of delivery personnel and a phase model for area division. Objectives are set for each phase. The first phase determines the total number of delivery personnel, with the corresponding objective being to minimize the total number of delivery personnel. The second phase determines the static area division, with the corresponding objective being to achieve task balance.

[0062] Among them, the models of the first stage and the second stage correspond to certain constraints respectively.

[0063] Furthermore, in one embodiment, the constraints of the model in the stage of determining the total number of dispatch personnel include: static area division constraints, static area population constraints, and inter-network enclave constraints; the constraints of the model in the stage of area division include: static area division constraints, static area population constraints, inter-network enclave constraints, total number of dispatch personnel constraints, and task balancing auxiliary constraints.

[0064] The static area division constraint in the model's constraints for determining the total number of delivery personnel includes the following: each delivery point within the current transit point's coverage area is assigned to exactly one static area. The static area headcount constraint includes the upper limit on the number of delivery personnel assigned to any static area. In one embodiment, this upper limit is set by obtaining historical shipment volume within the static area. The inter-point enclave constraint includes the following: enclaves are not permitted between any two delivery points within each static area. An enclave refers to land under the jurisdiction of a particular administrative district but not adjacent to the district. In this embodiment, enclaves are not permitted between delivery points within a static area, meaning that all delivery points within a static area must be geographically adjacent.

[0065] The static area division constraint, static area population constraint, and static area population constraint in the constraint conditions of the area division stage model are the same as the constraint conditions in the total number of delivery personnel determination stage model and will not be repeated here. The total number of delivery personnel constraint includes: the total number of delivery personnel is determined by the total number of delivery personnel determination stage model of the first stage. The task balance auxiliary constraint includes: the deviation between the task value assigned to each delivery personnel and the average task value is less than the preset deviation threshold; the task balance auxiliary constraint is used to constrain the upper limit of the difference between the task value of each delivery personnel and the average task value, that is, the difference between the task value assigned to any delivery personnel and the average task value shall not exceed the preset deviation threshold.

[0066] In the above embodiment, the static area division model is divided into two stages, namely determining the total number of dispatch personnel and dividing the static area, which reduces the difficulty of solving the model and improves the efficiency of model solving.

[0067] In one embodiment, when the number of unit areas contained in the static area does not exceed a preset threshold, the task allocation model includes a task packaging stage model and a post-processing model; the delivery task packaging stage model assigns delivery tasks to unit areas with the goal of task balance; the delivery task includes multiple unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned to the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0068] The static area is the area delineated by the static area partitioning model in the above steps. A static area includes at least one network point and at least one unit area. Within the static area, each unit area is assigned to a corresponding delivery person, and parcels within each unit area in a delivery task are delivered by the same delivery person. In one embodiment, if a static area contains only one unit area, the static area is directly assigned to a single delivery person. In another embodiment, if the number of unit areas within the static area is greater than one but does not exceed a preset threshold, task packaging can be performed directly within the static area. In other words, in this embodiment, the task assignment model is divided into a task packaging phase model and a post-processing model.

[0069] In one embodiment, the task packaging phase model is used to generate delivery tasks and "pack" as many unit areas as possible into the delivery tasks. Each delivery task corresponds to one delivery person, which is referred to as the generated tasks in this embodiment. After the task packaging phase model completes processing, it outputs the unit areas to be assigned to the generated tasks and unassigned tasks. The output includes information about which unit areas each generated task corresponds to.

[0070] Furthermore, in this embodiment, after the task packaging stage model outputs the generated tasks, there are still unassigned task areas that have not been assigned to tasks. In this case, the post-processing model will assign the unassigned tasks to the generated tasks with the goal of task balance, and finally generate a delivery task allocation plan in which all unit areas are assigned to delivery tasks.

[0071] In one embodiment, the delivery task allocation plan includes: the delivery tasks belonging to each unit area within the coverage of the current transfer station, or in other words, which unit areas are respectively included in the delivery tasks included in the current transfer station.

[0072] Further, both the task packing stage model and the post-processing model aim to balance the tasks. The task balance in this embodiment is the same as the task balance in the above embodiments, which will not be described again. Understandably, due to the constraints of reality, there are certain constraints, task balance auxiliary constraints, on the number of delivery items for each delivery task, the weight of the delivery express, and the like, which can be determined according to actual conditions. In an embodiment, the upper limit of the difference in the task balance auxiliary constraints in the post-processing model can be adjusted appropriately.

[0073] In another embodiment, if the number of unit areas included in the static area exceeds the preset threshold, the static area is first divided into two or more candidate areas, and then the candidate areas are subjected to task packing. In this embodiment, the task allocation model includes a candidate area division stage model, a task packing stage model, and a post-processing model.

[0074] Further, in this embodiment, the candidate area division stage model aims to minimize the sum of distances between unit areas in the candidate area to divide the static area into two or more candidate areas; and any candidate area includes two or more unit areas. The task packing stage model aims to balance the tasks to attribute the unit areas in each candidate area to a delivery task.

[0075] In this embodiment, the number of unit areas in a static area exceeds the preset threshold, and the static area is first divided into a smaller range of areas, which are referred to as candidate areas in this embodiment. Then, task packing and post-processing are performed in the candidate areas. That is, the task allocation model in this embodiment includes a candidate area division stage model, a task packing stage model, and a post-processing model.

[0076] The candidate area division stage model is used to divide the static area into two or more candidate areas. In this embodiment, when the candidate area division stage model divides the areas, it should avoid the formation of enclaves in a candidate area, that is, two unit areas in a candidate area should be adjacent in geography. In this embodiment, the sum of distances between unit areas is minimized as an objective to ensure that two unit areas in a candidate area are adjacent in geography and will not form enclaves. Further, in an embodiment, the distance between two unit areas can be represented by the distance between the centers of the two unit areas. The preset threshold corresponding to the number of unit areas in the static area can be set to, for example, 200, 100, and the like according to actual conditions.

[0077] It can be understood that the task packaging stage model and post-processing model in this embodiment are similar to the task packaging stage model and post-processing model in the above embodiment. The only difference is that the task packaging model in this embodiment performs task packaging on the unit areas in the subsequent area, while in the embodiment where the unit areas in the static area do not exceed the preset threshold, the task packaging model directly performs task packaging on the unit areas in the static area.

[0078] In one embodiment, the task packaging model is used to generate delivery tasks and "pack" as many unit areas as possible within the candidate region into the delivery tasks. Each delivery task corresponds to one delivery person, which is referred to as the generated task in this embodiment. After the task packaging model completes processing, it outputs the unit areas to which the generated tasks and unassigned tasks are assigned. The output includes the corresponding unit areas for each generated task.

[0079] Furthermore, in this embodiment, after the task packaging stage model outputs the generated tasks, there are still unassigned task areas that have not been assigned to tasks. In this case, the post-processing model will assign the unassigned tasks to the generated tasks with the goal of task balance, and finally generate a delivery task allocation plan in which all unit areas are assigned to delivery tasks.

[0080] In one embodiment, the delivery task allocation plan includes: the delivery tasks belonging to each unit area within the coverage of the current transfer station, or in other words, which unit areas are respectively included in the delivery tasks included in the current transfer station.

[0081] Furthermore, both the task packaging phase model and the post-processing model aim for task balance; the task balance here is identical to the task balance discussed in the above-mentioned embodiments and will not be further elaborated upon. Understandably, due to real-world constraints, each delivery task has certain constraints, such as the number of items delivered and the weight of the items delivered, as well as auxiliary task balance constraints. These constraints can be determined based on actual conditions. In one embodiment, the upper limit of the difference in the auxiliary task balance constraints in the post-processing model can be adjusted appropriately.

[0082] In this embodiment, when the coverage range of the static area contains a large number of unit areas, the static area is first divided, and then task packaging and post-processing are performed in the candidate areas within the smaller range obtained by the division. When the coverage range of the static area contains a large number of unit areas, the candidate areas are first divided and then task packaging and post-processing are performed. This can reduce the difficulty of solving the model and improve the efficiency of model solving.

[0083] Furthermore, in one embodiment, the constraints of the candidate area division stage model include: candidate area division constraints, candidate area quantity constraints, candidate area piece quantity constraints and candidate area weight constraints; the constraints of the task packaging stage model include: packaging constraints, total number of delivery personnel constraints, task piece quantity constraints, task weight constraints, delivery task area range constraints, enclave constraints between unit areas, and task balance auxiliary constraints; the constraints of the post-processing model include: task attribution uniqueness constraints, task attribution distance constraints and task balance auxiliary constraints.

[0084] The candidate area division constraints in the candidate area division model include: each unit area is divided into one and only one candidate area. The candidate area quantity constraint is used to limit the upper limit of the number of candidate area divisions. It is understandable that this upper limit can be set to any value greater than 1 based on actual conditions. The candidate area quantity constraint and candidate area weight constraint are used to limit the upper limit of the number and weight of express parcels within each candidate area, respectively.

[0085] The packing constraints in the task packing model include: each candidate area can be assigned to at most one delivery task. The total number of delivery personnel constraint includes: the total number of delivery personnel in all candidate areas within a static area must be the same as the total number of delivery personnel output by the static area partitioning model. The task quantity constraint and task weight constraint are used to limit the upper limit of the number and weight of parcels within each delivery task, respectively. The quantity and weight constraints primarily aim to ensure that the number and weight of parcels within each delivery task assigned to a delivery personnel cannot be excessive. Therefore, during task packing, quantity and weight constraints are set for each delivery task. The delivery task area scope constraint includes: for each generated delivery task. The inter-unit enclave constraint includes: enclaves are not allowed between the unit areas within any generated delivery task. Auxiliary task balancing constraints include: the deviation between the task value assigned to each delivery personnel and the per capita task value must be less than a preset deviation threshold. The auxiliary task balancing constraint caps the difference between each delivery personnel's task value and the per capita task value, i.e., the difference between the task value assigned to any delivery personnel and the per capita task value must not exceed a preset deviation threshold.

[0086] It should be noted that if the task allocation model only includes the task packaging stage model and the post-processing model, each unit area will be regarded as a candidate area.

[0087] In this embodiment, constraints corresponding to specific stages are set for each stage model of the task allocation model. Under the premise of these constraints, the corresponding goals of each stage are solved to obtain respective output results.

[0088] In one specific embodiment, the static region partitioning model's total number of dispatch personnel determination phase model and region partitioning phase model, as well as the task allocation model's candidate region partitioning phase model, task packaging phase model, and post-processing model can be implemented using any solver, such as CPLEX (a mathematical optimization technique) or Gurobi (a large-scale mathematical programming optimizer). In this embodiment, the solver solves each phase model in stages according to the optimization objective, quickly obtaining a dispatch task allocation plan with low solution difficulty and improved solution efficiency.

[0089] like Figure 2 The following are the specific steps of a delivery task assignment method in a specific embodiment. In this embodiment, a specific heavy package is used as an example. The overall goal of delivery task assignment is to ensure a balanced total value for each delivery person's delivery tasks. This prevents delivery persons from receiving excessively different values ​​due to factors such as the number and weight of packages included in their delivery tasks, thereby facilitating overall management of the transit station.

[0090] In this embodiment, the distribution of delivery tasks is divided into two major stages: the division of static areas and the distribution of tasks.

[0091] Static Zone Division: Static zones are the intermediate level between transfer stations and unit areas. They are essentially a virtual concept, created to facilitate transfer station management and subsequent task allocation. Static zone division is based on network points and aims to balance the tasks of delivery personnel.

[0092] Task allocation: Task allocation is carried out in each static area, with the unit area as the basic unit and the goal of balancing the task value of the dispatch personnel.

[0093] In this embodiment, the above-mentioned delivery task allocation method includes the following steps:

[0094] Obtain the number of heavy items in each unit area of ​​the current transfer site, the recipient address of each heavy item, and the network information covered by the current transfer site.

[0095] A static area division model and a task allocation model are constructed separately, and corresponding constraints are set. The solutions are solved with their respective corresponding objectives to obtain the delivery task allocation plan for heavy items within the current transfer yard coverage, as well as the required number of delivery personnel. From the delivery task allocation plan, it can be known which unit areas will be assigned to the same delivery task, and the heavy items in the unit areas within the same delivery task will be delivered by the same delivery personnel, so that the delivery task can be assigned to a specific delivery personnel.

[0096] Since static regional division is a prerequisite for task allocation and the goal is to balance the tasks of delivery personnel, the total number of delivery personnel in all regions must be determined first to determine the average task value per person. The goal of task value balance is then achieved by minimizing the average deviation of the delivery personnel's task value (the average of the absolute difference between each delivery personnel's task value and the average task value per person). The static regional division model consists of two stages: the stage model for determining the total number of delivery personnel and the stage model for regional division.

[0097] Phase 1: Determine the total number of delivery personnel Phase model:

[0098] Decision variables:

[0099] 1)x i,j : Whether point i is the center of the static area where point j is located

[0100] 2)p i : Number of delivery personnel in static area i

[0101] Constraints:

[0102] 1) Partition constraint: Each node is divided into one and only one static region;

[0103] 2) Regional headcount constraint: Determine the number of delivery personnel in a region based on the volume of parcels in a static region;

[0104] 3) Enclave constraint: Enclaves are not allowed among the nodes in each static area, that is, they must be geographically adjacent.

[0105] Optimization goal: minimize the total number of delivery personnel (i.e. optimize manpower).

[0106] Phase II: Regional Division Phase Model:

[0107] Decision variables:

[0108] 1)x i,j :Same as the first stage

[0109] 2)p i :Same as the first stage

[0110] 3)Δ i : Auxiliary variable, the absolute value constraint of the difference between the task value of static region i and the average task value per capita in the region:

[0111] 1) Partitioning constraints: Same as the first stage;

[0112] 2) Regional population restrictions: Same as the first phase;

[0113] 3) Enclave constraints: Same as the first stage;

[0114] 4) Total number of people constraint: The total number of delivery personnel is equal to the optimization result of the first stage;

[0115] 5) Auxiliary constraint: Obtain the absolute value of the deviation of the task value of each static area to obtain the average deviation.

[0116] Optimization goal: minimize the average deviation of per capita task value (i.e. task value balance).

[0117] For the task allocation model, the basic unit is the unit area (as before), but due to the high efficiency requirements of the model and the large number of unit areas (possibly more than 200), it may be difficult to meet the efficiency requirements by directly solving the site selection model. Therefore, when the number of unit areas exceeds a certain number (the number limit is set artificially), the model is also divided into two stages for solution. The first stage is the candidate area division stage model, which aggregates the unit areas into several candidate areas; the second stage is the task packaging model, which packages the candidate areas with tasks; when the number of unit areas is small, the second stage packaging model is directly carried out, and the candidate areas are the unit areas. Finally, a post-processing step is added to the model results to assign tasks to the unpackaged unit areas to ensure that all unit areas have been allocated. Among them:

[0118] Phase 1: Candidate region division phase model:

[0119] Decision variable: y i,j : Whether unit area i is the center of the candidate area where unit area j is located

[0120] Constraints:

[0121] 1) Partition constraint: Each unit area is divided into one and only one candidate area;

[0122] 2) Total number of candidate regions (manually set);

[0123] 3) The upper limit of the number of pieces in the candidate area;

[0124] 4) Upper limit of the weight of the candidate region.

[0125] Optimization goal: Minimize the sum of the distances from the center of each candidate region to its internal unit area (avoiding the generation of enclaves within the candidate region).

[0126] Phase 2: Task Packaging Phase Model:

[0127] Decision variables:

[0128] 1)y i,j : Whether candidate region i is the center of the task area where candidate region j is located

[0129] 2)Δ i: Auxiliary variable, the absolute value of the difference between the task value of task i and the average task value per person

[0130] Constraints:

[0131] 1) Packing constraint: Each candidate region is assigned to at most one task;

[0132] 2) Total number of dispatch personnel;

[0133] 3) The upper limit of the number of tasks;

[0134] 4) The weight limit of the task;

[0135] 5) The upper limit of the mission area radius (distance limit);

[0136] 6) Enclave constraint: Enclaves are not allowed in candidate areas within each mission area, that is, they must be geographically adjacent;

[0137] 7) Auxiliary constraint: Obtain the absolute value of the deviation of the task value of each task to obtain the average deviation.

[0138] Optimization goal: minimize the average deviation of task value (i.e. task value balance).

[0139] Post-processing model:

[0140] Decision variables:

[0141] 1)y i,j : Whether unit area j is assigned to task i

[0142] 2)Δ i : Auxiliary variable, the absolute value of the difference between the task value of task i and the average task value per person

[0143] Constraints:

[0144] 1) Partitioning constraint: Each unassigned unit area is assigned to one and only one task;

[0145] 2) Distance restriction: For each unassigned unit area, the tasks that can be assigned must include one of the several unit areas closest to the unit area;

[0146] 3) Auxiliary constraint: Obtain the absolute value of the deviation of the task value of each task to obtain the average deviation.

[0147] Optimization goal: minimize the average deviation of task value (try not to destroy the balance of task value).

[0148] Among them, the enclave constraints of each stage model: Since the decision variable of the site selection model is x i,jIn the form of, that is, whether the basic unit i is the center of the area where the basic unit j is located, in order to avoid the emergence of enclaves, that is, to ensure that all basic units in the same area are adjacent, a set of enclave constraints need to be added, that is: the prerequisite for the basic unit i to become the center of the area where the basic unit j is located is that all distances i are less than d i,j The basic unit k of (the distance between i and j) must also be distributed within the area centered on i. The specific mathematical expression is as follows:

[0149]

[0150] Among them, P i,j If the distance i is less than d i,j The distance between i and j is the set of basic units, and I is the set of all basic units.

[0151] The reason why the task allocation model adopts a packing model rather than a partitioning model is that in the task allocation model, the total number of tasks (the total number of delivery personnel) is fixed, and the enclave constraint tends to plan the task area as a convex region. However, it is difficult to ensure that the entire area is divided into a fixed number of convex regions. Therefore, the packing model is adopted to "pack" as many candidate regions as possible into the delivery tasks. The unit regions corresponding to the remaining candidate regions without assigned tasks are assigned to the generated delivery tasks in the final post-processing stage.

[0152] The delivery task allocation method in the above embodiment realizes the hierarchical planning of direct delivery tasks (heavy items) at the transfer station, reducing the difficulty of task allocation and overall management; it strives to ensure that the task values ​​of the delivery tasks assigned to the delivery personnel are balanced as much as possible, facilitating management; the phased task allocation model reduces the difficulty of model solution and improves the efficiency of model solution; and avoids the generation of enclaves in static areas and task areas.

[0153] It should be understood that, although each step in each flow chart involved in the above-described embodiment is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless clearly stated herein, the execution of these steps does not have strict order restrictions, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each flow chart involved in the above-described embodiment can include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of the steps or stages in other steps or other steps.

[0154] In one embodiment, Figure 3As shown, a delivery task allocation device is provided, comprising: an information acquisition module 310, a static area division module 320, a task allocation model 330 and a task allocation module 340, wherein:

[0155] The information acquisition module 310 is configured to acquire specific express information of each unit area in the current transfer station and network point information of a network point covered by the current transfer station.

[0156] The static area division module 320 is configured to construct a static area division model according to the specific express information and the network point information, and determine two or more static areas in the coverage area of the current transfer station and the number of delivery personnel corresponding to each static area based on the static area division model, with the goal of task balance and minimum total number of delivery personnel.

[0157] The task allocation model 330 is configured to construct a task allocation model according to the static areas and the corresponding number of delivery personnel, and determine a delivery task allocation plan for the unit areas in each static area to be assigned to a delivery task based on the task allocation model, with the goal of task balance.

[0158] The task allocation module 340 is configured to determine the corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0159] The above-mentioned delivery task allocation device first acquires specific express information of each unit area in the current transfer station and information of a network point covered by the current transfer station, constructs a static area division model according to the specific express information and the network point information, and divides the coverage area of the current transfer station into two or more static areas and allocates the number of delivery personnel to each static area based on the static area division model, with the goal of minimum total number of delivery personnel and task balance. Then, the task allocation model is constructed based on the number of delivery personnel corresponding to each static area, and the task allocation model is used to allocate tasks in each static area, with the goal of task balance, so as to obtain a delivery task allocation plan for the unit areas to be assigned to a delivery task. Finally, the corresponding delivery personnel for the delivery task is determined according to the delivery task allocation plan. The above-mentioned device divides the task allocation into two stages, first divides the large area covered by the transfer station into multiple static areas with the goal of minimum number of delivery personnel, and then allocates the delivery task in the static area with the goal of task balance, which not only ensures the minimum number of delivery personnel, but also ensures the task balance among the delivery personnel, so as to reduce the overall management difficulty of the transfer station.

[0160] The specific limitations of the task delivery device can refer to the limitations of the task delivery method described above, which will not be repeated here. Each module in the task delivery device described above can be implemented by software, hardware and their combination in whole or in part. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor calls to execute the operations corresponding to each of the above modules.

[0161] In one embodiment, a computer device, which can be a terminal, has an internal structure diagram as shown in Figure 4 The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected by a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The communication interface of the computer device is used to communicate with external terminals in wired or wireless mode. Wireless mode can be achieved through WIFI, operator network, NFC (near field communication) or other technologies. The computer program is executed by the processor to implement a task delivery method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad provided on the shell of the computer device. It can also be an external keyboard, touchpad or mouse, etc.

[0162] Those skilled in the art can understand that Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0163] In one embodiment, a computer device is provided, which includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the following steps:

[0164] Obtain specific express delivery information of each unit area in the current transfer yard and the network information of the network points covered by the current transfer yard; construct a static area division model based on the specific express delivery information and network point information, and based on the static area division model, determine two or more static areas within the coverage area of ​​the current transfer yard, as well as the number of delivery personnel corresponding to each static area, with the goal of task balance and minimization of the total number of delivery personnel; construct a task allocation model based on the static areas and the corresponding number of delivery personnel, and based on the task allocation model, determine the delivery task allocation plan for the unit areas within each static area that belong to the delivery task with the goal of task balance; determine the corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0165] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the static area division model includes a total number of dispatch personnel determination stage model and an area division stage model; the goal of the total number of dispatch personnel determination stage model is to minimize the total number of dispatch personnel, and the goal of the area division stage model is task balance.

[0166] In one embodiment, when the processor executes the computer program, the following steps are further implemented: the constraints of the model in the stage of determining the total number of dispatch personnel include: static area division constraints, static area population constraints, and inter-network enclave constraints; the constraints of the model in the stage of area division include: static area division constraints, static area population constraints, inter-network enclave constraints, total number of dispatch personnel constraints, and task balancing auxiliary constraints.

[0167] In one embodiment, the processor further implements the following steps when executing the computer program: when the number of unit areas contained in the static area does not exceed a preset threshold, the task allocation model includes a task packaging stage model and a post-processing model; the delivery task packaging stage model assigns delivery tasks to unit areas with the goal of task balance; the delivery task includes multiple unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned of the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0168] In one embodiment, the processor further implements the following steps when executing the computer program: when the number of unit areas contained in the static area exceeds a preset threshold, the task allocation model includes a candidate area division stage model, a task packaging stage model and a post-processing model; the candidate area division stage model divides the static area into two or more candidate areas with the goal of minimizing the sum of distances between the unit areas in the candidate area; any candidate area contains more than two unit areas; the task packaging stage model assigns delivery tasks to each candidate area with the goal of task balance; the delivery task includes more than two unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned of the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0169] In one embodiment, when the processor executes the computer program, the following steps are further implemented: the constraint conditions of the candidate area division stage model include: candidate area division constraint, candidate area number constraint, candidate area piece quantity constraint and candidate area weight constraint; the constraint conditions of the task packaging stage model include: packaging constraint, total number of delivery personnel constraint, task piece quantity constraint, task weight constraint, delivery task area range constraint, enclave constraint between unit areas, and task balance auxiliary constraint; the constraint conditions of the post-processing model include: task attribution unique constraint, task attribution distance constraint and task balance auxiliary constraint.

[0170] In one embodiment, when the processor executes the computer program, the following steps are further implemented: the goal of task balancing includes: minimizing the average deviation between the task value assigned to each delivery person and the average task value per person.

[0171] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0172] Obtain specific express delivery information of each unit area in the current transfer yard and the network information of the network points covered by the current transfer yard; construct a static area division model based on the specific express delivery information and network point information, and based on the static area division model, determine two or more static areas within the coverage area of ​​the current transfer yard, as well as the number of delivery personnel corresponding to each static area, with the goal of task balance and minimization of the total number of delivery personnel; construct a task allocation model based on the static areas and the corresponding number of delivery personnel, and based on the task allocation model, determine the delivery task allocation plan for the unit areas within each static area that belong to the delivery task with the goal of task balance; determine the corresponding delivery personnel for the delivery task according to the delivery task allocation plan.

[0173] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the static area division model includes a total number of dispatch personnel determination stage model and an area division stage model; the goal of the total number of dispatch personnel determination stage model is to minimize the total number of dispatch personnel, and the goal of the area division stage model is task balance.

[0174] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: the constraints of the model in the stage of determining the total number of dispatched personnel include: static area division constraints, static area population constraints, and inter-network enclave constraints; the constraints of the model in the stage of area division include: static area division constraints, static area population constraints, inter-network enclave constraints, total number of dispatched personnel constraints, and task balancing auxiliary constraints.

[0175] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the number of unit areas contained in the static area does not exceed a preset threshold, the task allocation model includes a task packaging stage model and a post-processing model; the delivery task packaging stage model assigns delivery tasks to unit areas with the goal of task balance; the delivery task includes multiple unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned of the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0176] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the number of unit areas contained in the static area exceeds a preset threshold, the task allocation model includes a candidate area division stage model, a task packaging stage model and a post-processing model; the candidate area division stage model divides the static area into two or more candidate areas with the goal of minimizing the sum of distances between the unit areas in the candidate area; any candidate area contains more than two unit areas; the task packaging stage model assigns delivery tasks to each candidate area with the goal of task balance; the delivery task includes more than two unit areas; the post-processing model obtains the generated tasks output by the delivery task packaging stage model, as well as the unit areas to be assigned of the unassigned tasks; with the goal of task balance, the unit areas to be assigned are assigned to the generated tasks.

[0177] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: the constraint conditions of the candidate area division stage model include: candidate area division constraint, candidate area number constraint, candidate area piece quantity constraint and candidate area weight constraint; the constraint conditions of the task packaging stage model include: packaging constraint, total number of delivery personnel constraint, task piece quantity constraint, task weight constraint, delivery task area range constraint, enclave constraint between unit areas, and task balance auxiliary constraint; the constraint conditions of the post-processing model include: task attribution unique constraint, task attribution distance constraint and task balance auxiliary constraint.

[0178] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: the goal of task balancing includes: minimizing the average deviation between the task value assigned to each delivery person and the average task value per person.

[0179] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0180] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0181] The above embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A delivery task allocation method, characterized in that: The method comprises: Obtain specific express information for each unit area within the current transfer station and network information of the network points covered by the current transfer station; Constructing a static area division model based on the specific express delivery information and the network point information, and determining two or more static areas within the current transfer station coverage area and the number of delivery personnel corresponding to each static area based on the static area division model with the goal of balancing tasks and minimizing the total number of delivery personnel; Constructing a task allocation model based on the static areas and the corresponding number of delivery personnel, and determining a delivery task allocation plan for assigning delivery tasks to unit areas within each static area based on the task allocation model with a goal of task balance; Corresponding delivery personnel are determined for the delivery tasks based on the delivery task allocation plan. The static area division model includes a total number of delivery personnel determination phase model and an area division phase model. The objective of the total number of delivery personnel determination phase model is to minimize the total number of delivery personnel, and the objective of the area division phase model is to balance tasks. Constraints of the total number of delivery personnel determination phase model include: static area division constraints, static area population constraints, and inter-point enclave constraints. Constraints of the area division phase model include: static area division constraints, static area population constraints, inter-point enclave constraints, total number of delivery personnel constraints, and auxiliary task balance constraints.

2. The method according to claim 1, characterized in that When the number of unit areas contained in the static area does not exceed a preset threshold, the task allocation model includes a task packaging phase model and a post-processing model; The delivery task packing phase model assigns delivery tasks to unit areas with the goal of task balance; the delivery task includes multiple unit areas; The post-processing model obtains the generated tasks output by the delivery task packaging phase model, and the to-be-assigned unit areas of the unassigned tasks; With the goal of task balance, the unit area to be assigned is assigned to the generated task.

3. The method according to claim 2, characterized in that When the number of unit areas contained in the static area exceeds the preset threshold, the task allocation model includes a candidate area division stage model, a task packaging stage model and a post-processing model; The candidate region division model divides the static region into two or more candidate regions with the goal of minimizing the sum of distances between unit regions within the candidate region; any candidate region contains two or more unit regions; The task packing stage model assigns delivery tasks to each candidate area with the goal of task balance; the delivery task includes more than two unit areas; The post-processing model obtains the generated tasks output by the delivery task packaging phase model, and the to-be-assigned unit areas of the unassigned tasks; With the goal of task balance, the unit area to be assigned is assigned to the generated task.

4. The method according to claim 3, wherein: The constraint conditions of the candidate area division model include: candidate area division constraint, candidate area quantity constraint, candidate area quantity constraint and candidate area weight constraint; The constraints of the task packing stage model include: packing constraint, total number of delivery personnel constraint, task quantity constraint, task weight constraint, delivery task area scope constraint, inter-unit area enclave constraint, and task balance auxiliary constraint; The constraints of the post-processing model include: task attribution uniqueness constraint, task attribution distance constraint and task balance auxiliary constraint.

5. The method according to claim 1, characterized in that The objectives of task balancing include minimizing the average deviation between the task value assigned to each delivery person and the average task value per person.

6. The method according to claim 1, characterized in that The task balance auxiliary constraint includes: the deviation between the task value assigned to each delivery personnel and the average task value is less than a preset deviation threshold. The task balance auxiliary constraint is used to constrain the upper limit of the difference between the task value of each delivery personnel and the average task value.

7. The method according to claim 1, characterized in that The solutions to the stage model for determining the total number of delivery personnel and the stage model for dividing the regions are obtained by using a CPLEX solver or a Gurobi solver.

8. A delivery task allocation device, characterized in that: The device comprises: The information acquisition module is used to obtain specific express information of each unit area in the current transfer station and the network information of the network covered by the current transfer station; A static area division module is configured to construct a static area division model based on the specific express delivery information and the outlet information, and based on the static area division model, determine two or more static areas within the current transfer yard coverage area, and the number of delivery personnel corresponding to each static area, with the goal of balancing tasks and minimizing the total number of delivery personnel; A task allocation model is used to construct a task allocation model based on the static areas and the corresponding number of delivery personnel, and based on the task allocation model, determine a delivery task allocation plan for assigning unit areas within each static area to delivery tasks with a goal of task balance; A task allocation module is configured to determine corresponding delivery personnel for delivery tasks based on the delivery task allocation plan. The static area division model includes a total number of delivery personnel determination phase model and an area division phase model. The objective of the total number of delivery personnel determination phase model is to minimize the total number of delivery personnel, and the objective of the area division phase model is to achieve task balance. Constraints in the total number of delivery personnel determination phase model include: static area division constraints, static area population constraints, and inter-node enclave constraints. Constraints in the area division phase model include: static area division constraints, static area population constraints, inter-node enclave constraints, total number of delivery personnel constraints, and auxiliary task balance constraints.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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