Method, device, computer equipment and medium for generating collection and dispatch manpower planning scheme

Abstract

The present application relates to a method, device, computer equipment and storage medium for generating a collection and dispatch manpower planning scheme, wherein the method includes obtaining historical operation data of outlets, analyzing the number of collection and dispatch personnel in daily historical unit areas, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, and further determining the priority evaluation index threshold of the unit area based on these data using a convex optimization method to determine the priority that the collection and dispatch manpower planning of different unit areas meets, and planning the manpower demand forecast results corresponding to different unit areas according to the priority, thereby generating collection and dispatch manpower planning schemes for different unit areas. During the whole process, corresponding collection and dispatch manpower planning schemes are generated for different unit areas in the outlets; in addition, the priority evaluation index threshold of the unit area is reasonably analyzed based on the historical operation data of the outlets, so as to determine the planning priority, which can ensure the accuracy of the collection and dispatch manpower planning scheme.

Description

Technical Field

[0001] The present application relates to the field of intelligent dispatching technology, and in particular to a method, device, computer equipment and storage medium for generating a collection and dispatch manpower planning solution. Background Art

[0002] With the development of Internet technology and logistics technology, the demand for manpower in the logistics field is increasing. The accuracy and stability of collection and delivery manpower planning has always been an operational issue that the logistics field has been committed to solving.

[0003] The human resource planning for delivery involves the planning of the number of front-line delivery personnel. It can provide regions with a pre-emptive and reliable human resource investment implementation plan and help regions plan recruitment plans in advance to meet the growing business needs. However, efficient and reasonable human resource planning for delivery needs to balance the relationship between recruitment costs and whether the output efficiency of personnel can meet business needs. It should neither invest too much to cause redundant personnel and increase operating costs, nor invest too little to cause the business needs of increasing volume of parcels to be unmet.

[0004] The planning results of traditional collection and delivery manpower planning schemes partially rely on fixed data from manual surveys rather than dynamic parameters, and are unable to restore the current situation with changes. Therefore, it is impossible to obtain an accurate collection and delivery manpower planning scheme. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment and storage medium for generating a collection and dispatch manpower planning plan that can generate an accurate collection and dispatch manpower planning plan in response to the above technical problems.

[0006] A method for generating a collection and dispatch manpower planning scheme, the method comprising:

[0007] Obtain historical operation data of outlets;

[0008] Based on the historical operation data of the outlets, analyze the daily historical unit area collection and delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0009] According to the daily historical number of dispatchers in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area;

[0010] Determine the priority of the collection and dispatch manpower planning in different unit areas according to the priority evaluation index threshold;

[0011] According to the priority of the collection and dispatch manpower planning in different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated.

[0012] In one of the embodiments, analyzing the daily historical number of receiving and delivering personnel in a unit area based on the historical operation data of outlets includes: extracting the attendance hours of receiving and delivering personnel, the number of receiving and delivering waybills of the outlets, the number of receiving and delivering waybills of each unit area, and the number of receiving and delivering personnel and unit area belonging to the same outlet based on the historical operation data of outlets; analyzing the monthly historical business volume data based on the historical operation data of outlets includes: obtaining historical waybill data and extracting the information on the outlets to which each waybill belongs and the operation information based on the historical operation data of the network, converting the information on the outlets to which each waybill belongs and the operation information into spatial GIS data, obtaining the unit area to which each waybill belongs, grouping the waybills belonging to the same unit area, and obtaining the monthly historical business volume of the unit area.

[0013] In one embodiment, according to the daily historical number of dispatchers in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area, including:

[0014] The daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data are embedded in the convex optimization model, and the convex optimization method is used to analyze the month-on-month business increment threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio.

[0015] In one embodiment, according to the daily historical number of dispatchers in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area, including:

[0016] Analyze the influencing variables of delivery manpower planning based on the daily historical unit area delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0017] According to the influencing variables, the convex optimization method is used to construct the objective function of unit area optimization, and the constraints of the influencing variables are determined according to the application scenarios of receiving and delivering parcels in the unit area of ​​the network point;

[0018] According to the objective function and constraints, and with the maximum month-on-month business increase and the minimum collection and dispatch ratio corresponding to the highest collection and dispatch staff efficiency as the optimization goal, optimization is performed to solve the month-on-month business increase threshold, the collection and dispatch staff efficiency threshold, and the minimum optimized collection and dispatch ratio threshold.

[0019] In one embodiment, the priority evaluation indicator thresholds include a business month-on-month increment threshold, a collection and dispatch personnel efficiency threshold, and a minimum optimized collection and dispatch ratio threshold; the first priority condition is lower than the business month-on-month increment threshold, higher than the collection and dispatch personnel efficiency threshold, and higher than the minimum optimized collection and dispatch ratio threshold; the second priority condition is higher than the business month-on-month increment threshold and lower than the minimum optimized collection and dispatch ratio threshold;

[0020] According to the priority evaluation index threshold, the priorities of the collection and dispatch manpower planning in different unit areas are determined as follows:

[0021] According to the first priority condition and the second priority condition, the priority conditions met by the collection and dispatch manpower planning of different unit areas are determined based on the mutual exclusion principle. The priority conditions include meeting the first priority condition, not meeting the first priority condition, meeting the second priority condition, and not meeting the second priority condition.

[0022] In one embodiment, according to the priorities of the collection and dispatch manpower planning of different unit areas, the manpower demand forecast results corresponding to the different unit areas are planned, and the collection and dispatch manpower planning schemes for the different unit areas are generated, including:

[0023] When the unit area is a unit area that meets the first priority condition, the business volume forecast value of the unit area in the future preset month is obtained to obtain the first business volume forecast value, and the manpower demand forecast result of the unit area is obtained according to the first business volume forecast value and the efficiency threshold of the delivery personnel of the unit area;

[0024] When the unit area is a unit area that does not meet the first priority condition, the number of delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area;

[0025] When the unit area is a unit area that meets the second priority condition, the business volume forecast value of the unit area for the month is obtained to obtain the second business volume forecast value, and the manpower demand forecast result of the unit area is obtained according to the second business volume forecast value and the efficiency threshold of the delivery personnel of the unit area;

[0026] When the unit area is a unit area that does not meet the second priority condition, the number of delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area;

[0027] Based on the manpower demand forecast results of the unit area, generate the collection and dispatch manpower planning plan for the unit area.

[0028] In one embodiment, generating a collection and dispatch manpower planning scheme for different unit areas includes:

[0029] Obtain the number of full-time workers, part-time workers, and mobile manpower input ratios in the unit area in the historical records, and obtain the number of waybills completed by full-time workers and part-time workers in the unit area in the historical records;

[0030] According to the number of waybills completed by full-time workers and part-time workers, the probability of a single waybill being assigned to a full-time worker is obtained, and according to the manpower demand forecast results of the planned unit area, the total manpower demand of the unit area is obtained;

[0031] According to the probability of a single waybill being assigned to full-time workers, the number of full-time workers and part-time workers, and the total labor demand, the probability of the total labor demand containing different numbers of full-time workers is obtained;

[0032] Obtain the number of full-time workers corresponding to the maximum probability that the total manpower demand includes different numbers of full-time workers, and obtain the target number of full-time workers;

[0033] According to the total labor demand and the target number of full-time workers, the target number of part-time workers is obtained;

[0034] Generate a collection and dispatch manpower planning plan for the unit area based on the target number of full-time workers, target number of part-time workers, and the ratio of flexible manpower input.

[0035] A device for generating a collection and dispatch manpower planning scheme, the device comprising:

[0036] Historical data acquisition module, used to obtain historical operation data of outlets;

[0037] The data analysis module is used to analyze the number of daily historical unit area collection and delivery personnel, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data based on the historical operation data of the outlets;

[0038] The indicator threshold determination module is used to determine the priority evaluation indicator threshold of the unit area using a convex optimization method based on the daily historical number of unit area pickup and dispatch personnel, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0039] The priority determination module is used to determine the priorities of the collection and dispatch manpower planning of different unit areas according to the priority evaluation index threshold;

[0040] The scheme generation module is used to plan the manpower demand forecast results corresponding to different unit areas according to the priorities of the collection and dispatch manpower planning of different unit areas, and generate the collection and dispatch manpower planning schemes for different unit areas.

[0041] 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:

[0042] Obtain historical operation data of outlets;

[0043] Based on the historical operation data of the outlets, analyze the daily historical unit area collection and delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0044] According to the daily historical number of dispatchers in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area;

[0045] Determine the priority of the collection and dispatch manpower planning in different unit areas according to the priority evaluation index threshold;

[0046] According to the priority of the collection and dispatch manpower planning in different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated.

[0047] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0048] Obtain historical operation data of outlets;

[0049] Based on the historical operation data of the outlets, analyze the daily historical unit area collection and delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0050] According to the daily historical number of dispatchers in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area;

[0051] Determine the priority of the collection and dispatch manpower planning in different unit areas according to the priority evaluation index threshold;

[0052] According to the priority of the collection and dispatch manpower planning in different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated.

[0053] The above-mentioned method, device, computer equipment and storage medium for generating the collection and dispatch manpower planning scheme obtain the historical operation data of the outlets, analyze the daily historical number of collection and dispatch personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data and the monthly service quality data, and further use the convex optimization method based on these data to determine the threshold value of the priority evaluation index of the unit area, so as to determine the priority that the collection and dispatch manpower planning of different unit areas meets, and plan the corresponding manpower demand forecast results of different unit areas according to the priority, so as to generate the collection and dispatch manpower planning scheme for different unit areas. During the whole process, corresponding collection and dispatch manpower planning schemes are generated for different unit areas in the outlets to ensure the rationality and pertinence of the schemes; in addition, the threshold value of the priority evaluation index of the unit area is reasonably analyzed based on the historical operation data of the outlets to determine the planning priority, so as to ensure the accuracy of the collection and dispatch manpower planning scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 An application environment diagram of a method for generating a collection and dispatch manpower planning solution in one embodiment;

[0055] Figure 2 A schematic diagram of a flow chart of a method for generating a collection and dispatch manpower planning solution in one embodiment;

[0056] Figure 3 A flowchart of a method for generating a collection and dispatch manpower planning solution in another embodiment;

[0057] Figure 4 A schematic diagram of manpower demand forecasting results for different priority unit areas in one embodiment;

[0058] Figure 5 It is a structural block diagram of a device for generating a collection and dispatch manpower planning scheme in one embodiment;

[0059] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0061] The method for generating a collection and dispatch manpower planning scheme provided in this application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The terminal 102 sends a request to generate a collection and dispatch manpower planning scheme to the server 104, and the server 104 responds to the request and obtains the historical operation data of the outlets; according to the historical operation data of the outlets, the number of collection and dispatch personnel in the daily historical unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data are analyzed; according to the number of collection and dispatch personnel in the daily historical unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area; according to the priority evaluation index threshold, the priority of the collection and dispatch manpower planning of different unit areas is determined; according to the priority of the collection and dispatch manpower planning of different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices, and the server 104 can be implemented with an independent server or a server cluster composed of multiple servers. It can be understood that the collection and dispatch manpower planning scheme generation method of the present application can also be executed separately on the terminal, which stores the historical operation data of the outlets, executes the complete collection and dispatch manpower planning scheme generation method, and finally obtains the collection and dispatch manpower planning scheme, which can be directly displayed.

[0062] In one embodiment, Figure 2 As shown, a method for generating a collection and dispatch manpower planning scheme is provided, and the method is applied to Figure 1 Taking the server 104 in the example as an example, the following steps are included:

[0063] S100: Obtain historical operation data of outlets.

[0064] Outlets refer to outlets for receiving and delivering parcels in the logistics system. They are very important as the "first kilometer" and "last kilometer" of the entire logistics system. In actual applications, a single outlet corresponds to serving multiple unit areas. The most common single outlet serves multiple communities and neighborhoods. Outlet historical operation data refers to the data on outlet operations in historical records, which mainly include the unit areas served by the outlets, the number of outlet collection and delivery personnel (number of couriers), the number of collection and delivery personnel serving each unit area, the outlet business volume, the daily / monthly collection and delivery personnel efficiency, and the collection / delivery waybill data received by the outlets. In this way, historical operation data characterizes the operation of the outlets in historical records, and it can also contain more types of data based on the data of actual application scenarios.

[0065] S200: Based on the historical operation data of the outlets, analyze the daily historical number of collection and delivery personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data.

[0066] Daily refers to the daily unit, that is, recording the data corresponding to each day; monthly refers to the monthly unit, that is, recording / collecting the data corresponding to each month. Here, the historical operation data of the outlets are analyzed, and the number of collection and delivery personnel in the daily historical unit area, the monthly historical business volume, the monthly historical performance data, and the monthly service quality data corresponding to the outlets are analyzed. Among them, the number of collection and delivery personnel in the daily historical unit area is the number of collection and delivery personnel (couriers) who serve the same unit area every day; the monthly historical business volume data is the number of collection / delivery waybills of the entire outlet / each unit area in units of months; the monthly historical performance data refers to the overall performance of the entire outlet / each unit area in units of months, specifically the monthly average of the ratio of daily historical business volume data to the daily number of collection and delivery personnel; the monthly service quality data refers to the ratio of the number of collection / delivery waybills received to the total number of collection / delivery waybills, which is used to quantify the service quality of the entire outlet (the higher the proportion of collection / delivery waybills, the lower the customer satisfaction of the outlet, and the worse the service quality of the outlet).

[0067] S300: According to the daily historical number of dispatching personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data and the monthly service quality data, a convex optimization method is used to determine the priority evaluation index threshold of the unit area.

[0068] According to the daily historical unit area delivery personnel number, monthly historical business volume data, monthly historical efficiency data and monthly service quality data determined by S200, the threshold of the priority evaluation index of each unit area is determined. Specifically, based on the data determined by S200, the priority evaluation index of the unit area is determined, and then the specific values ​​corresponding to these indicators are analyzed, and the thresholds corresponding to these evaluation indicators are found with reference to the historical data. In actual applications, after S200 processing, the intermediate data related to the waybill in the unit area dimension is produced through statistical analysis and spatial mapping. According to the relevant regulations of regional assessment, we collected information and found that the three most important indicators for the completion of regional work are: 1) employee service quality; 2) business (order volume) growth; 3) employee delivery efficiency. These three aspects fully describe the quality and quantity requirements that each outlet and employee needs to achieve in their work. Therefore, we choose these three indicators as the definition of the key reference indicators for the delivery manpower deployment. The thresholds and standards of these three indicators are further determined by convex optimization.

[0069] S400: Determine the priorities to be met by the collection and dispatch manpower planning of different unit areas according to the priority evaluation index threshold.

[0070] According to the priority evaluation index and the corresponding index threshold, the priority of the collection and dispatch manpower planning of different unit areas is determined. Specifically, taking the priority evaluation index threshold as the standard, the unit area is evaluated from different index levels, and then the priority of the collection and dispatch manpower planning corresponding to the unit area is determined based on the level of the unit area at different index levels. Further, as mentioned above, the evaluation indicators include 1) employee service quality; 2) business (order volume) growth; 3) employee collection and dispatch efficiency. Correspondingly, the priority of the collection and dispatch manpower planning of different unit areas can be evaluated from the three aspects of service quality, business growth rate and employee collection and dispatch efficiency based on the corresponding threshold. Specifically, it is judged that the business growth rate index threshold (business month-on-month increment threshold) is greater than the business growth rate index threshold as a high business growth rate, and the business growth rate is less than the business growth rate index threshold as a low business growth rate; it is judged that it is greater than the employee collection and dispatch efficiency index as high efficiency; it is judged that it is less than the service quality index (collection / dispatch ratio) as high service quality, and it is greater than the service quality index as low service quality.

[0071] S500: According to the priorities of the collection and dispatch manpower planning of different unit areas, the manpower demand forecast results corresponding to the different unit areas are planned, and the collection and dispatch manpower planning schemes for the different unit areas are generated.

[0072] Based on the priorities of the collection and dispatch manpower planning for different unit areas obtained in S400, the manpower demand determination method corresponding to different unit areas is determined, and then the manpower demand forecast result is obtained, and the collection and dispatch manpower planning schemes for different unit areas are generated. After the collection and dispatch manpower planning schemes for different unit areas are coordinated and arranged, the collection and dispatch manpower planning schemes for the outlets are obtained.

[0073] The above-mentioned method for generating the collection and dispatch manpower planning scheme obtains the historical operation data of the outlets, analyzes the daily historical number of collection and dispatch personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data, and further uses the convex optimization method based on these data to determine the threshold value of the priority evaluation index of the unit area, so as to determine the priority of the collection and dispatch manpower planning of different unit areas, and plan the corresponding manpower demand forecast results of different unit areas according to the priority, so as to generate the collection and dispatch manpower planning scheme for different unit areas. In the whole process, the corresponding collection and dispatch manpower planning schemes are generated for different unit areas in the outlets to ensure the rationality and pertinence of the scheme; in addition, the threshold value of the priority evaluation index of the unit area is reasonably analyzed based on the historical operation data of the outlets, so as to determine the planning priority, which can ensure the accuracy of the collection and dispatch manpower planning scheme.

[0074] In one of the embodiments, analyzing the daily historical number of receiving and delivering personnel in a unit area based on the historical operation data of outlets includes: extracting the attendance hours of receiving and delivering personnel, the number of receiving and delivering waybills of the outlets, the number of receiving and delivering waybills of each unit area, and the number of receiving and delivering personnel and unit area belonging to the same outlet based on the historical operation data of outlets; analyzing the monthly historical business volume data based on the historical operation data of outlets includes: obtaining historical waybill data and extracting the information on the outlets to which each waybill belongs and the operation information based on the historical operation data of the network, converting the information on the outlets to which each waybill belongs and the operation information into spatial GIS data, obtaining the unit area to which each waybill belongs, grouping the waybills belonging to the same unit area, and obtaining the monthly historical business volume of the unit area.

[0075] The following will use specific letters and formulas to explain in detail the definitions of the daily historical unit area delivery personnel number, monthly historical business volume data, monthly historical performance data, and monthly service quality data and their corresponding specific data.

[0076] a. Daily historical unit area delivery personnel number (number of people / number of couriers)

[0077] Traditional historical data on the number of delivery personnel is only detailed to the branch level, and it is impossible to directly obtain data at the unit area level. It is necessary to restore the unit area headcount data through the delivery personnel's attendance hours and the distribution of delivery volume.

[0078] After the collection, the following specific data can be obtained:

[0079] Number of delivery personnel assigned to a certain outlet: X j ∈N, j=1, ..., A;

[0080] Unit area belonging to a certain network point: Y j ∈N, j=1, ..., A;

[0081] Daily attendance time of a delivery person at a branch: T j ∈∞,j=1,2,3...n;

[0082] Number of waybills received by the delivery personnel in a certain unit area every day: S i ∈N,i=1,2,3....m,

[0083] Number of delivery orders: P i ∈N,i=1,2,3....m

[0084] Number of waybills collected and delivered by the delivery personnel at a certain outlet every day: N j ∈N,j=1,2,3....n

[0085] The attendance time W of the unit area follows a uniform distribution: W~U(w,T), where w jj∈∞

[0086] Thus through The number of people in the restored daily unit area = ∑ j ∑ j W jj ÷8, the first j represents a unit area, the second j represents the delivery personnel who have delivery orders in the unit area, and 8 represents the required daily working hours of full-time delivery personnel. The final output is the number of delivery personnel per day at the unit area level, which represents the actual number of personnel required in the unit area.

[0087] b. Monthly historical business volume data

[0088] The current business volume is calculated based on the outlets. In order to obtain the historical business volume at the unit area level with finer granularity, spatial conversion and hierarchical mapping are required. According to the existing waybill-attributed outlet information and operation information, it is converted into spatial GIS data information to produce the unit area information to which the waybill belongs.

[0089] Specifically, the monthly historical business volume data for different unit areas may include the following steps: first, restore the collection and delivery routing data to the collection and delivery operation location dimension; then determine the operation longitude and latitude through the collection and delivery operation location dimension, and use it as the collection and delivery location; then, through the method of structural data space conversion, map the two-dimensional operation longitude and latitude data into spatial data, and at the same time, through the boundary intersection on the map, map the unit area boundaries that the system has divided into to the spatial map, and outline the spatial scope of the unit area; through the distribution of spatial images, the unit area to which the longitude and latitude data belong in the spatial position is output, thereby determining the unit area to which each historical waybill belongs.

[0090] In practical applications, the calculation steps of the above processing are as follows:

[0091] 1. Restore the delivery route data: restore to the FVP operation dimension, such as (50, 54) and other operations;

[0092] 2. Use FVP to locate the gun operator and confirm the longitude and latitude (L1, L2) as the pickup and delivery location;

[0093] 3. Through the method of structural data space conversion, the (L1, L2) two-dimensional data is mapped to spatial data. At the same time, through the boundary intersection on the map, the unit area boundary that the system has divided is mapped to the spatial map to outline the spatial range of the unit area. Through the distribution of the spatial image, the unit area to which (L1, L2) belongs in the spatial position is output, so as to determine the unit area to which each historical waybill belongs. Monthly historical business volume data = ∑ waybills belonging to the unit area.

[0094] c. Monthly historical performance data

[0095] The monthly historical performance of a unit area is used to describe the number of waybills that can be completed per person per month in each unit area.

[0096] d. Monthly service quality data

[0097] The premise of service quality evaluation is that the service of each outlet and unit area needs to be maintained at a certain stable level. Monthly service quality data is used to evaluate the service quality of the unit area in completing the current business volume. The current solution version takes the collection and dispatch situation as the core consideration of service quality. Among them, t-1 is the month before the current month, and t-3 is the three months before the current month. For example, if it is currently June, then t-1 is May and t-3 is March.

[0098] In one embodiment, according to the daily historical number of dispatchers in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area, including:

[0099] The daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data are embedded in the convex optimization model, and the convex optimization method is used to analyze the month-on-month business increment threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio.

[0100] The scenario of manpower deployment for collection and dispatch is embedded in the convex optimization model. Through the convex optimization method, the minimum amount of collection and dispatch that can be generated when the maximum business volume and the highest employee efficiency are achieved is obtained. This result is specifically used to characterize the thresholds of the three indicators of employee service quality, business growth, and collection and dispatch personnel efficiency.

[0101] like Figure 3 As shown, in one embodiment, S300 includes:

[0102] S320: Analyze the influencing variables of the delivery manpower planning based on the daily historical number of delivery personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data.

[0103] The variables that influence the collection and delivery manpower planning refer to the variables that affect the collection and delivery manpower planning. They mainly include variables in three aspects: business increment, efficiency ratio of collection and delivery personnel, and service quality. Specifically, they include the month-on-month increment of business in the unit area, efficiency weight of collection and delivery personnel in the unit area, and the proportion of collection and delivery. The above three variables will be introduced in detail below.

[0104] Month-on-month increase in unit area business: Xi ∈(0,1),i=1,2,3,4...., i represents different unit areas, and t represents different months. Unit area delivery personnel efficiency weight: that is, the efficiency of the delivery personnel in the spatial unit area, the quantile X of the efficiency ranking of all delivery personnel j ∈(0,1),j=1,2,3,4..., j represents different delivery personnel (couriers) in the unit area. Specifically, the delivery personnel in each unit area perform independent delivery, so the efficiency of each person is different. The quantile refers to the order of the efficiency of all delivery personnel from small to large. For example, there are 10 delivery personnel in total, and their 10 efficiency values ​​are ordered from small to large. The quantile of the delivery personnel with the largest efficiency value is 100%, and the quantile of the delivery personnel with the fifth highest efficiency is 50%. The quantile corresponds to their efficiency weights. The proportion of collection and delivery Y i ∈(0,1),i=1,2,3,4...., i is the unit area, t is the current month. In the scenario of indicator threshold, X i ,,X j , Y i The relationship between is constructed into a model function, and finally the business month-on-month increment threshold X is obtained. i , the efficiency weight of the delivery personnel, that is, the best percentile X of the delivery personnel efficiency ranking j (Exhibit collection and dispatch personnel efficiency), and the minimum optimized collection and dispatch ratio Y i .

[0105] S340: Based on the influencing variables, a convex optimization method is used to construct an objective function for unit area optimization, and the constraints of the influencing variables are determined based on the application scenario of receiving and delivering parcels in the unit area of ​​the network point.

[0106] In order to maximize the operating profit of the outlets, the convex optimization method is used to construct the business efficiency function of the unit area according to the influencing variables, and this function is used as the objective function. The maximum value of the objective function is obtained through optimization in subsequent actions. Specifically, the objective function is shown in the following formula:

[0107]

[0108] Moreover, α can make the inequality hold: f(α i X i +α j X j )≤α i f(X i )+α j f(X j ).

[0109] Constraints refer to the constraints between the unit area data and the entire network data in the delivery application scenario, that is, the unit area data must be within the scope of the network data constraints. Specific constraints include the following:

[0110] 1. Month-on-month increase in business in the unit area <= Month-on-month increase in business at the affiliated outlets

[0111]

[0112] 2. The efficiency of a certain delivery person in the unit area is <= 100% percentile of the efficiency ranking of the delivery persons in the affiliated outlets

[0113] X j ≤max(X j ,j=1,2,3...,A)

[0114] 3. The delivery personnel working across different units have the same working status in different units. When the delivery workload is saturated, the efficiency they generate is also equivalent to effi.

[0115]

[0116] S360: Optimize according to the objective function and constraints, and take the maximum month-on-month business increase and the minimum collection and dispatch ratio corresponding to the highest collection and dispatch personnel efficiency as the optimization goal, and solve the month-on-month business increase threshold, the collection and dispatch personnel efficiency threshold, and the minimum optimized collection and dispatch ratio threshold.

[0117] Based on the above data, the optimization goal is to maximize the month-on-month increase in business and the highest collection and delivery personnel efficiency to win the minimum collection and delivery ratio. The entire objective function is optimized to obtain the month-on-month increase threshold for business, the collection and delivery personnel efficiency threshold, and the minimum optimized collection and delivery ratio threshold. The collection and delivery personnel efficiency threshold is calculated using the collection and delivery personnel efficiency weight X j Characterization, that is, finally solving the ideal business growth threshold X i , the efficiency weight of the delivery personnel is X j , and the minimum optimized collection and dispatch ratio Y i .

[0118] In one embodiment, the priority evaluation indicator thresholds include a business month-on-month increment threshold, a collection and dispatch personnel efficiency threshold, and a minimum optimized collection and dispatch ratio threshold; the first priority condition is lower than the business month-on-month increment threshold, higher than the collection and dispatch personnel efficiency threshold, and higher than the minimum optimized collection and dispatch ratio threshold; the second priority condition is higher than the business month-on-month increment threshold and lower than the minimum optimized collection and dispatch ratio threshold;

[0119] According to the priority evaluation index threshold, determining the priority that the collection and dispatch manpower planning of different unit areas must meet includes: according to the first priority condition and the second priority condition, determining the priority that the collection and dispatch manpower planning of different unit areas must meet based on the mutual exclusion principle, and the priority conditions include meeting the first priority condition, not meeting the first priority condition, meeting the second priority condition, and not meeting the second priority condition.

[0120] In actual applications, the above three indicators corresponding to different unit areas are prioritized. The performance of each unit area is lower than the threshold as a low indicator, and higher than the threshold as a high indicator. Then, according to the following optimization of the screening rules of the three indicators, the unit area conditions are screened. The specific screening content is shown in Table 1 below.

[0121] Table 1 Priorities corresponding to different indicators

[0122] Priority 1 Priority 2 Service Quality Indicators Low service quality High service quality Business growth indicators Low business growth High business growth Performance Indicators High performance --

[0123] It should be pointed out that the above-mentioned priority situation is determined based on the principle of mutual exclusion, that is, different unit areas have only one priority situation, and different unit areas can be one of the priority situations of satisfying the first priority condition, not satisfying the first priority condition, satisfying the second priority condition, and not satisfying the second priority condition.

[0124] In one embodiment, according to the priorities of the collection and dispatch manpower planning of different unit areas, the manpower demand forecast results corresponding to the different unit areas are planned, and the collection and dispatch manpower planning schemes for the different unit areas are generated, including:

[0125] When the unit area is a unit area that meets the first priority condition, the business volume forecast value of the unit area for the future preset month is obtained to obtain the first business volume forecast value, and the manpower demand forecast result of the unit area is obtained based on the first business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the first priority condition, the number of collection and delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area; when the unit area is a unit area that meets the second priority condition, the business volume forecast value of the unit area for the current month is obtained to obtain the second business volume forecast value, and the manpower demand forecast result of the unit area is obtained based on the second business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the second priority condition, the number of collection and delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area; based on the manpower demand forecast result of the unit area, a collection and delivery manpower planning plan for the unit area is generated.

[0126] The manpower demand forecast results based on historical data can be different for different unit areas to meet different priority situations. This is used as a principle to plan the manpower demand forecast results corresponding to different unit areas. The above-mentioned future preset months can be 2 months or 3 months, preferably 2 months. In actual applications, the manpower demand forecast results of the above-mentioned different priority unit areas are as follows: Figure 4 Specifically, it corresponds to the following:

[0127] 1) To meet the priority 1 unit area, manpower demand = T+2 month forecast volume / belonging business area efficiency threshold;

[0128] 2) If the priority 1 unit area is not met, the manpower demand = the bottom line data, that is, the number of people in the unit area in T-1 month;

[0129] 1) and 2) are used to calculate the manpower requirements for T+2 month;

[0130] 3) For priority 2 unit areas, manpower requirements = corresponding monthly forecasted number of pieces / performance threshold of the business area;

[0131] 4) If the priority 2 unit area is not met, the manpower demand = the bottom line data, that is, the number of people in the unit area in T-1 month;

[0132] 3) and 4) are used to calculate the manpower requirements from T+3 to T+13.

[0133] Combining 1), 2), 3) and 4) we can get the manpower demand forecast for the next 12 months in month T.

[0134] In one embodiment, generating a collection and dispatch manpower planning scheme for different unit areas includes:

[0135] Obtain the number of full-time and part-time manpower in the unit area and the ratio of mobile manpower input in the historical records, and obtain the number of waybills completed by full-time and part-time manpower in the unit area in the historical records; obtain the probability of a single waybill being assigned to full-time manpower based on the number of waybills completed by full-time and part-time manpower, and obtain the total manpower demand in the unit area based on the manpower demand forecast result of the planned unit area; obtain the probability that the total manpower demand contains different numbers of full-time manpower based on the probability that a single waybill is assigned to full-time manpower, the number of full-time and part-time manpower, and the total manpower demand; obtain the number of full-time manpower corresponding to the maximum probability of containing different numbers of full-time manpower in the total manpower demand, and obtain the target number of full-time manpower; obtain the target number of part-time manpower based on the total manpower demand and the target number of full-time manpower; generate a collection and dispatch manpower planning plan for the unit area based on the target number of full-time manpower, the target number of part-time manpower, and the ratio of mobile manpower input.

[0136] Specifically, the forecast of manpower demand is the result of the dimension of the number of receiving and dispatching personnel, that is, a decimal value like 5.2 people will be produced, which represents the future manpower demand, but cannot be used as a reliance for the execution of regional recruitment (regional recruitment requires an integer number of people): Number of recruits = Unit area manpower input plan – Current manpower input. Under normal circumstances, the unit area contains three types of full-time manpower, part-time manpower and mobile manpower.

[0137] Full-time and part-time staffing options

[0138] Number of full-time employees: X i ∈N, i=1,...,A,i represents the unit area

[0139] Full-time manpower to complete the collection and delivery volume: M i ∈N, i=1,..., n,i represents the unit area

[0140] Number of part-time employees: Y i ∈N, i=1,...,A, i represents the unit area

[0141] The amount of parcels collected and delivered by part-time workers: Ni∈N, i=1,..., n,i represents the unit area

[0142] In order to determine the allocation ratio from the fractional value of manpower demand to full-time, part-time, and mobile, the historical collection and delivery volume completed by full-time and part-time manpower is analyzed. i =X i +Y i , the probability that a waybill is assigned to a full-time delivery person is p, p i =M i / (M i +N i ), then the future prediction of the situation where there are X full-time employees among the total N manpower follows the binomial distribution, and the probability P of this situation is:

[0143]

[0144] For k=1,2,3,4…N, we can get the k value corresponding to the maximum probability P value:

[0145] Number of full-time employees = k; number of part-time employees = floor (demand forecast result) - k.

[0146] Flexible human resources deployment plan

[0147] In order to meet the real-life scenario of full-time and part-time employee scheduling, the historical average allocation is calculated based on the historical full-time and flexible allocation ratios. This value is obtained through analysis of historical data. Different outlets / unit areas have different historical operating data, so their corresponding weights and mobile ratios will be different. That is, 6 full-time workers are assigned to one mobile worker. Thus, a mobile worker input plan is generated. Combining the above full-time and part-time human resources input plans and mobile human resources input plans, an accurate collection and dispatch manpower planning plan can be obtained in the end.

[0148] It should be understood that, although the steps in the above-mentioned flowcharts are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above-mentioned flowcharts may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0149] like Figure 5 As shown, the present application also provides a device for generating a collection and dispatch manpower planning scheme, the device comprising:

[0150] The historical data acquisition module 100 is used to acquire the historical operation data of the outlets;

[0151] The data analysis module 200 is used to analyze the number of daily historical unit area delivery personnel, monthly historical business volume data, monthly historical efficiency data and monthly service quality data based on the historical operation data of the outlets;

[0152] The index threshold determination module 300 is used to determine the priority evaluation index threshold of the unit area by using a convex optimization method according to the daily historical number of dispatchers in the unit area, the monthly historical business volume data, the monthly historical efficiency data and the monthly service quality data;

[0153] The priority determination module 400 is used to determine the priorities to be met by the collection and dispatch manpower planning of different unit areas according to the priority evaluation index threshold;

[0154] The scheme generating module 500 is used to plan the manpower demand forecast results corresponding to different unit areas according to the priorities of the manpower planning for receiving and dispatching different unit areas, and generate manpower planning schemes for receiving and dispatching different unit areas.

[0155] The above-mentioned collection and dispatch manpower planning scheme generation device obtains the historical operation data of the outlets, analyzes the daily historical number of collection and dispatch personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data and the monthly service quality data, and further uses the convex optimization method based on these data to determine the priority evaluation index threshold of the unit area, so as to determine the priority of the collection and dispatch manpower planning of different unit areas, and plans the corresponding manpower demand forecast results of different unit areas according to the priority, so as to generate the collection and dispatch manpower planning scheme for different unit areas. During the whole process, corresponding collection and dispatch manpower planning schemes are generated for different unit areas in the outlets to ensure the rationality and pertinence of the scheme; in addition, the priority evaluation index threshold of the unit area is reasonably analyzed based on the historical operation data of the outlets to determine the planning priority, so as to ensure the accuracy of the collection and dispatch manpower planning scheme.

[0156] In one of the embodiments, the data analysis module 200 is also used to extract the attendance hours of the collection and delivery personnel, the number of collection and delivery waybills of the outlets, the number of collection and delivery waybills of each unit area, and the number of collection and delivery personnel and unit areas belonging to the same outlet based on the historical operation data of the outlets; based on the historical operation data of the network, obtain the historical waybill data and extract the outlet information and operation information of each waybill, convert the outlet information and operation information of each waybill into spatial GIS data, obtain the unit area to which each waybill belongs, group the waybills belonging to the same unit area, and obtain the monthly historical business volume of the unit area.

[0157] In one of the embodiments, the indicator threshold determination module 300 is also used to embed the daily historical unit area collection and delivery personnel number, monthly historical business volume data, monthly historical efficiency data and monthly service quality data into a convex optimization model, and use a convex optimization method to analyze the business month-on-month incremental threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio.

[0158] In one of the embodiments, the indicator threshold determination module 300 is also used to analyze the influencing variables of the collection and delivery manpower planning based on the daily historical number of collection and delivery personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data; based on the influencing variables, a convex optimization method is used to construct the objective function of the unit area optimization, and the constraints of the influencing variables are determined according to the application scenario of the collection and delivery of parcels in the unit area of ​​the outlets; according to the objective function and the constraints, and with the maximum business month-on-month increase and the minimum collection and delivery ratio corresponding to the highest collection and delivery personnel efficiency as the optimization goal, the optimization is performed to solve the business month-on-month increase threshold, the collection and delivery personnel efficiency threshold, and the minimum optimized collection and delivery ratio threshold.

[0159] In one embodiment, the priority evaluation indicator thresholds include a business month-on-month increment threshold, a collection and dispatch personnel efficiency threshold, and a minimum optimized collection and dispatch ratio threshold; the first priority condition is lower than the business month-on-month increment threshold, higher than the collection and dispatch personnel efficiency threshold, and higher than the minimum optimized collection and dispatch ratio threshold; the second priority condition is higher than the business month-on-month increment threshold and lower than the minimum optimized collection and dispatch ratio threshold;

[0160] The priority determination module 400 is also used to determine the priority conditions that the collection and dispatch manpower planning of different unit areas meets based on the mutual exclusion principle according to the first priority condition and the second priority condition. The priority conditions include meeting the first priority condition, not meeting the first priority condition, meeting the second priority condition, and not meeting the second priority condition.

[0161] In one of the embodiments, the plan generation module 500 is also used to obtain the business volume forecast value of the unit area for a preset month in the future when the unit area is a unit area that meets the first priority condition, obtain the first business volume forecast value, and obtain the manpower demand forecast result of the unit area based on the first business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the first priority condition, obtain the number of collection and delivery personnel in the unit area in the previous month, and obtain the manpower demand forecast result of the unit area; when the unit area is a unit area that meets the second priority condition, obtain the business volume forecast value of the unit area for the current month, obtain the second business volume forecast value, and obtain the manpower demand forecast result of the unit area based on the second business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the second priority condition, obtain the number of collection and delivery personnel in the unit area in the previous month, and obtain the manpower demand forecast result of the unit area; based on the manpower demand forecast result of the unit area, generate a collection and delivery manpower planning plan for the unit area.

[0162] In one embodiment, the solution generation module 500 is also used to obtain the number of full-time manpower, the number of part-time manpower and the ratio of mobile manpower input in the unit area in the historical records, and obtain the number of waybills completed by full-time manpower and the number of waybills completed by part-time manpower in the unit area in the historical records; obtain the probability of a single waybill being assigned to full-time manpower based on the number of waybills completed by full-time manpower and the number of waybills completed by part-time manpower, and obtain the total manpower demand of the unit area based on the manpower demand forecast result of the planned unit area; obtain the probability that the total manpower demand contains different numbers of full-time manpower based on the probability that a single waybill is assigned to full-time manpower, the number of full-time manpower, the number of part-time manpower and the total manpower demand; obtain the number of full-time manpower corresponding to the maximum probability that the total manpower demand contains different numbers of full-time manpower, and obtain the target number of full-time manpower; obtain the target number of part-time manpower based on the total manpower demand and the target number of full-time manpower; generate a collection and dispatch manpower planning solution for the unit area based on the target number of full-time manpower, the target number of part-time manpower and the ratio of mobile manpower input.

[0163] For the specific limitations of the collection and dispatch manpower planning scheme generation device, please refer to the limitations of the collection and dispatch manpower planning scheme generation method above, which will not be repeated here. Each module in the above-mentioned collection and dispatch manpower planning scheme generation device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0164] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, 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, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store historical operation data of the outlets. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for generating a collection and dispatch manpower planning plan is implemented.

[0165] Those skilled in the art will understand that Figure 6The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0166] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0167] Obtain historical operation data of outlets;

[0168] Based on the historical operation data of the outlets, analyze the daily historical unit area collection and delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0169] According to the daily historical number of dispatchers in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area;

[0170] Determine the priority of the collection and dispatch manpower planning in different unit areas according to the priority evaluation index threshold;

[0171] According to the priority of the collection and dispatch manpower planning in different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated.

[0172] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0173] Based on the historical operation data of the outlets, the attendance hours of the collection and delivery personnel, the number of collection and delivery waybills of the outlets, the number of collection and delivery waybills of each unit area, and the number of collection and delivery personnel and unit areas belonging to the same outlet are extracted; based on the historical operation data of the network, the historical waybill data is obtained and the information on the outlets to which each waybill belongs and the operation information are extracted, and the information on the outlets to which each waybill belongs and the operation information are converted into spatial GIS data to obtain the unit area to which each waybill belongs, and the waybills belonging to the same unit area are grouped to obtain the monthly historical business volume of the unit area.

[0174] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0175] The daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data are embedded in the convex optimization model, and the convex optimization method is used to analyze the month-on-month business increment threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio.

[0176] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0177] According to the daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the influencing variables of collection and delivery manpower planning are analyzed; according to the influencing variables, the convex optimization method is used to construct the objective function of unit area optimization, and the constraints of the influencing variables are determined according to the application scenarios of collection and delivery in the unit area of ​​the outlets; according to the objective function and constraints, and with the maximum month-on-month business increase and the minimum collection and delivery ratio corresponding to the highest collection and delivery personnel efficiency as the optimization goal, the optimization is performed to solve the month-on-month business increase threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio threshold.

[0178] In one embodiment, the priority evaluation index thresholds include a business month-on-month increment threshold, a collection and dispatch personnel efficiency threshold, and a minimum optimized collection and dispatch ratio threshold; the first priority condition is lower than the business month-on-month increment threshold, higher than the collection and dispatch personnel efficiency threshold, and higher than the minimum optimized collection and dispatch ratio threshold; the second priority condition is higher than the business month-on-month increment threshold and lower than the minimum optimized collection and dispatch ratio threshold; when the processor executes the computer program, the following steps are also implemented:

[0179] According to the first priority condition and the second priority condition, the priority conditions met by the collection and dispatch manpower planning of different unit areas are determined based on the mutual exclusion principle. The priority conditions include meeting the first priority condition, not meeting the first priority condition, meeting the second priority condition, and not meeting the second priority condition.

[0180] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0181] When the unit area is a unit area that meets the first priority condition, the business volume forecast value of the unit area for the future preset month is obtained to obtain the first business volume forecast value, and the manpower demand forecast result of the unit area is obtained based on the first business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the first priority condition, the number of collection and delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area; when the unit area is a unit area that meets the second priority condition, the business volume forecast value of the unit area for the current month is obtained to obtain the second business volume forecast value, and the manpower demand forecast result of the unit area is obtained based on the second business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the second priority condition, the number of collection and delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area; based on the manpower demand forecast result of the unit area, a collection and delivery manpower planning plan for the unit area is generated.

[0182] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0183] Obtain the number of full-time and part-time manpower in the unit area and the ratio of mobile manpower input in the historical records, and obtain the number of waybills completed by full-time and part-time manpower in the unit area in the historical records; obtain the probability of a single waybill being assigned to full-time manpower based on the number of waybills completed by full-time and part-time manpower, and obtain the total manpower demand in the unit area based on the manpower demand forecast result of the planned unit area; obtain the probability that the total manpower demand contains different numbers of full-time manpower based on the probability that a single waybill is assigned to full-time manpower, the number of full-time and part-time manpower, and the total manpower demand; obtain the number of full-time manpower corresponding to the maximum probability of containing different numbers of full-time manpower in the total manpower demand, and obtain the target number of full-time manpower; obtain the target number of part-time manpower based on the total manpower demand and the target number of full-time manpower; generate a collection and dispatch manpower planning plan for the unit area based on the target number of full-time manpower, the target number of part-time manpower, and the ratio of mobile manpower input.

[0184] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0185] Obtain historical operation data of outlets;

[0186] Based on the historical operation data of the outlets, analyze the daily historical unit area collection and delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data;

[0187] According to the daily historical number of dispatchers in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the convex optimization method is used to determine the priority evaluation index threshold of the unit area;

[0188] Determine the priority of the collection and dispatch manpower planning in different unit areas according to the priority evaluation index threshold;

[0189] According to the priority of the collection and dispatch manpower planning in different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated.

[0190] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0191] Based on the historical operation data of the outlets, the attendance hours of the collection and delivery personnel, the number of collection and delivery waybills of the outlets, the number of collection and delivery waybills of each unit area, and the number of collection and delivery personnel and unit areas belonging to the same outlet are extracted; based on the historical operation data of the network, the historical waybill data is obtained and the information on the outlets to which each waybill belongs and the operation information are extracted, and the information on the outlets to which each waybill belongs and the operation information are converted into spatial GIS data to obtain the unit area to which each waybill belongs, and the waybills belonging to the same unit area are grouped to obtain the monthly historical business volume of the unit area.

[0192] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0193] The daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data are embedded in the convex optimization model, and the convex optimization method is used to analyze the month-on-month business increment threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio.

[0194] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0195] According to the daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data, the influencing variables of collection and delivery manpower planning are analyzed; according to the influencing variables, the convex optimization method is used to construct the objective function of unit area optimization, and the constraints of the influencing variables are determined according to the application scenarios of collection and delivery in the unit area of ​​the outlets; according to the objective function and constraints, and with the maximum month-on-month business increase and the minimum collection and delivery ratio corresponding to the highest collection and delivery personnel efficiency as the optimization goal, the optimization is performed to solve the month-on-month business increase threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio threshold.

[0196] In one embodiment, the priority evaluation index thresholds include a business month-on-month increment threshold, a collection and dispatch personnel efficiency threshold, and a minimum optimized collection and dispatch ratio threshold; the first priority condition is lower than the business month-on-month increment threshold, higher than the collection and dispatch personnel efficiency threshold, and higher than the minimum optimized collection and dispatch ratio threshold; the second priority condition is higher than the business month-on-month increment threshold and lower than the minimum optimized collection and dispatch ratio threshold; when the computer program is executed by the processor, the following steps are also implemented:

[0197] According to the first priority condition and the second priority condition, the priority conditions met by the collection and dispatch manpower planning of different unit areas are determined based on the mutual exclusion principle. The priority conditions include meeting the first priority condition, not meeting the first priority condition, meeting the second priority condition, and not meeting the second priority condition.

[0198] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0199] When the unit area is a unit area that meets the first priority condition, the business volume forecast value of the unit area for the future preset month is obtained to obtain the first business volume forecast value, and the manpower demand forecast result of the unit area is obtained based on the first business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the first priority condition, the number of collection and delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area; when the unit area is a unit area that meets the second priority condition, the business volume forecast value of the unit area for the current month is obtained to obtain the second business volume forecast value, and the manpower demand forecast result of the unit area is obtained based on the second business volume forecast value and the efficiency threshold of the collection and delivery personnel in the unit area; when the unit area is a unit area that does not meet the second priority condition, the number of collection and delivery personnel in the unit area in the previous month is obtained to obtain the manpower demand forecast result of the unit area; based on the manpower demand forecast result of the unit area, a collection and delivery manpower planning plan for the unit area is generated.

[0200] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0201] Obtain the number of full-time and part-time manpower in the unit area and the ratio of mobile manpower input in the historical records, and obtain the number of waybills completed by full-time and part-time manpower in the unit area in the historical records; obtain the probability of a single waybill being assigned to full-time manpower based on the number of waybills completed by full-time and part-time manpower, and obtain the total manpower demand in the unit area based on the manpower demand forecast result of the planned unit area; obtain the probability that the total manpower demand contains different numbers of full-time manpower based on the probability that a single waybill is assigned to full-time manpower, the number of full-time and part-time manpower, and the total manpower demand; obtain the number of full-time manpower corresponding to the maximum probability of containing different numbers of full-time manpower in the total manpower demand, and obtain the target number of full-time manpower; obtain the target number of part-time manpower based on the total manpower demand and the target number of full-time manpower; generate a collection and dispatch manpower planning plan for the unit area based on the target number of full-time manpower, the target number of part-time manpower, and the ratio of mobile manpower input.

[0202] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned 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 can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can 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).

[0203] The technical features of the above embodiments may 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.

[0204] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for generating a collection and dispatch manpower planning scheme, characterized in that: The method comprises: Obtain historical operation data of outlets; Analyze the daily historical unit area delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data based on the historical operation data of the outlets; According to the daily historical number of collection and delivery personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data and the monthly service quality data, a convex optimization method is used to determine the priority evaluation index threshold of the unit area; the priority evaluation index threshold includes a business month-on-month increment threshold, a collection and delivery personnel efficiency threshold and a minimum optimized collection and delivery ratio threshold; Determine the priorities of the collection and dispatch manpower planning for different unit areas according to the priority evaluation index threshold; According to the priorities of the collection and dispatch manpower planning of different unit areas, the manpower demand forecast results corresponding to different unit areas are planned, and the collection and dispatch manpower planning schemes for different unit areas are generated.

2. The method according to claim 1, characterized in that Analyzing the number of delivery personnel in the daily historical unit area according to the historical operation data of the outlets includes: extracting the attendance time of delivery personnel, the number of delivery waybills of the outlets, the number of delivery waybills of each unit area, and the number of delivery personnel and unit area belonging to the same outlet according to the historical operation data of the outlets; According to the historical operation data of the outlets, analyzing the monthly historical business volume data includes: according to the historical operation data of the outlets, obtaining historical waybill data and extracting the outlet information and operation information of each waybill, converting the outlet information and operation information of each waybill into spatial GIS data, obtaining the unit area to which each waybill belongs, aggregating the waybills belonging to the same unit area, and obtaining the monthly historical business volume of the unit area.

3. The method according to claim 1, characterized in that The method of determining the priority evaluation index threshold of the unit area by using the convex optimization method according to the daily historical number of unit area delivery personnel, monthly historical business volume data, monthly historical efficiency data and monthly service quality data includes: The daily historical number of collection and delivery personnel in the unit area, monthly historical business volume data, monthly historical efficiency data and monthly service quality data are embedded in the convex optimization model, and the convex optimization method is used to analyze the month-on-month business increment threshold, the collection and delivery personnel efficiency threshold and the minimum optimized collection and delivery ratio threshold.

4. The method according to claim 1, characterized in that: The method of determining the priority evaluation index threshold of the unit area by using the convex optimization method according to the daily historical number of unit area delivery personnel, monthly historical business volume data, monthly historical efficiency data and monthly service quality data includes: Analyze the influencing variables of the delivery manpower planning based on the daily historical unit area delivery personnel number, monthly historical business volume data, monthly historical efficiency data, and monthly service quality data; According to the influencing variables, a convex optimization method is used to construct an objective function for unit area optimization, and the constraint conditions of the influencing variables are determined according to the application scenario of receiving and delivering parcels in the unit area of ​​the network point; According to the objective function and the constraints, and with the maximum month-on-month business increase and the minimum collection and dispatch ratio corresponding to the highest collection and dispatch personnel efficiency as the optimization goals, optimization is performed to solve the month-on-month business increase threshold, the collection and dispatch personnel efficiency threshold and the minimum optimized collection and dispatch ratio threshold.

5. The method according to claim 1, characterized in that The first priority condition is lower than the business month-on-month increment threshold, higher than the collection and dispatch personnel efficiency threshold and higher than the minimum optimized collection and dispatch ratio threshold; the second priority condition is higher than the business month-on-month increment threshold and lower than the minimum optimized collection and dispatch ratio threshold; Determining the priorities of the collection and dispatch manpower planning of different unit areas according to the priority evaluation index threshold includes: According to the first priority condition and the second priority condition, the priority conditions that must be met by the collection and dispatch manpower planning of different unit areas are determined based on the principle of mutual exclusion, and the priority conditions include meeting the first priority condition, not meeting the first priority condition, meeting the second priority condition, and not meeting the second priority condition.

6. The method according to claim 5, characterized in that The planning of the manpower demand forecast results corresponding to different unit areas according to the priorities of the collection and dispatch manpower planning of different unit areas, and the generation of collection and dispatch manpower planning schemes for different unit areas include: When the unit area is a unit area that meets the first priority condition, a business volume forecast value of the unit area in a preset month in the future is obtained to obtain a first business volume forecast value, and a manpower demand forecast result of the unit area is obtained according to the first business volume forecast value and the efficiency threshold of the delivery personnel of the unit area; When the unit area is a unit area that does not meet the first priority condition, the number of delivery personnel in the unit area in the previous month is obtained to obtain a manpower demand forecast result of the unit area; When the unit area is a unit area that meets the second priority condition, the business volume forecast value of the unit area for the current month is obtained to obtain the second business volume forecast value, and the manpower demand forecast result of the unit area is obtained according to the second business volume forecast value and the efficiency threshold of the delivery personnel of the unit area; When the unit area is a unit area that does not meet the second priority condition, the number of delivery personnel in the unit area in the previous month is obtained to obtain a manpower demand forecast result of the unit area; Based on the manpower demand forecast results of the unit area, generate the collection and dispatch manpower planning plan for the unit area.

7. The method according to claim 1, characterized in that Generating collection and dispatch manpower planning solutions for different unit areas includes: Obtain the number of full-time workers, part-time workers, and mobile manpower input ratios in the unit area in the historical records, and obtain the number of waybills completed by full-time workers and part-time workers in the unit area in the historical records; According to the number of waybills completed by full-time workers and part-time workers, the probability of a single waybill being assigned to a full-time worker is obtained, and according to the manpower demand forecast results of the planned unit area, the total manpower demand of the unit area is obtained; According to the probability of a single waybill being assigned to full-time workers, the number of full-time workers and part-time workers, and the total labor demand, the probability of the total labor demand containing different numbers of full-time workers is obtained; Obtain the number of full-time workers corresponding to the maximum probability that the total manpower demand includes different numbers of full-time workers, and obtain the target number of full-time workers; Obtaining a target number of part-time workers according to the total labor demand and the target number of full-time workers; A collection and dispatch manpower planning scheme for a unit area is generated according to the target number of full-time manpower, the target number of part-time manpower and the flexible manpower input ratio.

8. A device for generating a collection and dispatch manpower planning scheme, characterized in that: The device comprises: Historical data acquisition module, used to obtain historical operation data of outlets; A data analysis module, for analyzing the number of daily historical unit area collection and delivery personnel, monthly historical business volume data, monthly historical efficiency data and monthly service quality data based on the historical operation data of the outlets; An indicator threshold determination module is used to determine the priority evaluation indicator threshold of the unit area by using a convex optimization method according to the daily historical number of collection and delivery personnel in the unit area, the monthly historical business volume data, the monthly historical efficiency data, and the monthly service quality data; the priority evaluation indicator threshold includes a business month-on-month increment threshold, a collection and delivery personnel efficiency threshold, and a minimum optimized collection and delivery ratio threshold; A priority determination module, used to determine the priorities to be met by the collection and dispatch manpower planning of different unit areas according to the priority evaluation index threshold; The scheme generation module is used to plan the manpower demand forecast results corresponding to different unit areas according to the priorities of the collection and dispatch manpower planning of different unit areas, and generate collection and dispatch manpower planning schemes for different unit areas.

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.

Images