Method, device, computer equipment and storage medium for optimizing express delivery capacity

Abstract

The present application relates to a method, device, computer equipment and storage medium for optimizing express delivery capacity. The method includes: determining the trunk capacity and branch line capacity according to the arrival sites of each capacity; generating a trunk capacity achievable timeliness data table for the trunk capacity and a branch line capacity achievable timeliness data table corresponding to the branch line capacity according to the timeliness of historical waybills; when it is determined that there is a timeliness risk in the waybill, determining a timeliness rescue data table from the branch line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill; determining the optimal capacity of the waybill according to the timeliness rescue data table. The use of this method can ensure that the risk of delays in waybills is reduced, and makes the determined optimal capacity more objective, thereby improving accuracy.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, computer equipment and storage medium for optimizing express delivery capacity. Background Art

[0002] Express delivery is the foundation of the logistics industry, and the timeliness of express delivery is also crucial to its impact. However, since the entire circulation process of express delivery is very complicated, there will inevitably be some force majeure factors that affect the timeliness of express delivery. These impacts usually directly bring about the risk of customer complaints and increase costs. Therefore, it is particularly important to provide the best transportation capacity for express delivery to reduce the risk of express delivery delays or even customer complaints. The current recommendation for the best transportation capacity for express delivery is to plan the entire optimal path after the waybill is issued. This method can improve the timeliness to a certain extent.

[0003] However, the traditional method of planning the entire optimal path for the waybill only provides the theoretical optimal subsequent transportation capacity for the waybill, which reduces the accuracy. Summary of the invention

[0004] Based on this, it is necessary to provide an optimization method, device, computer equipment and storage medium for express delivery capacity that can improve accuracy in response to the above technical problems.

[0005] A method for optimizing express delivery capacity, characterized in that the method comprises:

[0006] Determine trunk and branch line capacity based on the arrival sites of each capacity;

[0007] Generate a data table of achievable time efficiency of trunk line capacity and a data table of achievable time efficiency of branch line capacity corresponding to the branch line capacity respectively according to the time efficiency of historical waybills;

[0008] When it is determined that there is a timeliness risk in the waybill, a timeliness saving data table is determined from the feeder line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill;

[0009] The optimal transport capacity of the waybill is determined according to the time-saving data table.

[0010] In one embodiment, a trunk line capacity achievable time efficiency data table of the trunk line capacity is generated according to the historical waybill time efficiency, including:

[0011] Obtain each loading city corresponding to the trunk line capacity;

[0012] Count the historical waybill volumes of each district and county under each loading city within the first preset time, and filter out the remote districts and counties of each loading city to obtain the valid districts and counties of each loading city;

[0013] Counting the historical waybill volume carried by the trunk line transport capacity for each of the valid counties of each of the loading cities within the second preset time, and determining the loading cities that can be covered by the trunk line transport capacity from each of the loading cities;

[0014] Obtaining the planned dispatch time of the trunk transport capacity, and respectively counting the historical waybills of the trunk transport capacity for each of the covered loading cities;

[0015] Calculate the achievable time for the trunk line capacity to reach each of the covered loading cities based on the historical waybill time of each of the covered loading cities and the planned departure time;

[0016] A data table of achievable time efficiency of trunk line capacity is generated according to the basic capacity information of the trunk line capacity and the achievable time efficiency of reaching each of the coverable loading cities.

[0017] In one embodiment, a branch line capacity achievable time efficiency data table corresponding to the branch line capacity is generated according to the historical waybill time efficiency, including:

[0018] Obtain each loading network point corresponding to the branch line capacity;

[0019] Respectively count the historical waybills of the branch line transport capacity for each of the loading outlets, and obtain the planned dispatch time of the branch line transport capacity;

[0020] Calculate the difference between the 80th percentile of the historical waybill time efficiency corresponding to each of the loading outlets and the planned departure time to obtain the achievable time efficiency of the branch line capacity arriving at each of the loading outlets;

[0021] A data table of achievable time efficiency of branch line capacity is generated according to the basic capacity information of the branch line capacity and the achievable time efficiency of reaching each of the loading outlets.

[0022] In one embodiment, when it is determined that there is a timeliness risk in the waybill, determining the timeliness saving data table from the branch line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill includes:

[0023] When it is determined that there is a timeliness risk in the waybill, the city where the waybill is currently located and the destination city of the waybill are obtained;

[0024] When the current transfer station city is consistent with the destination city, determining the branch line capacity achievable time efficiency data table as the time efficiency saving data table;

[0025] When the city of the current transfer station is inconsistent with the destination city, the trunk line capacity achievable time data table is determined as the time saving data table.

[0026] In one embodiment, when the time-saving data table is a branch line capacity achievable time-saving data table, determining the optimal capacity of the waybill according to the time-saving data table includes:

[0027] Based on the branch line capacity achievable time efficiency data table, select candidate branch line capacity including the destination network point of the waybill;

[0028] Obtain the latest arrival time of each candidate branch line capacity and the arrival time of the waybill at the current transfer yard;

[0029] Filter candidate branch line transport capacity whose latest arrival time of the line is after the arrival time to obtain optional branch line transport capacity;

[0030] The achievable time of the optional branch line transport capacity is obtained, the achievable time of each optional branch line transport capacity is compared, and the optional branch line transport capacity with the fastest time is determined as the optimal transport capacity of the waybill.

[0031] In one embodiment, when the time-saving data table is a trunk line capacity achievable time-saving data table, determining the optimal capacity of the waybill according to the time-saving data table includes:

[0032] Obtain the arrival time of the waybill at the current transfer station;

[0033] According to the achievable time efficiency data table of trunk transport capacity, a first candidate trunk transport capacity is selected where the loading city includes the destination city of the waybill but the destination city is different from the destination city of the waybill;

[0034] For trunk transport capacity with the same destination city as the destination city of the waybill, the trunk transport capacity of the destination transfer station including the destination outlet of the waybill is screened to obtain the second candidate trunk transport capacity;

[0035] Obtain the latest arrival time of the first candidate trunk line capacity and the second candidate trunk line capacity respectively;

[0036] Select the candidate trunk line capacity whose latest arrival time of the route is after the arrival time from the first candidate trunk line capacity and the second candidate trunk line capacity to obtain the optional trunk line capacity;

[0037] Obtain the achievable time of each of the optional trunk transport capacities, compare the achievable time of each of the optional trunk transport capacities, and determine the optional trunk transport capacity with the fastest time as the optimal transport capacity for the waybill.

[0038] In one embodiment, the method for determining whether a waybill has a timeliness risk includes:

[0039] Get the initial promised delivery time and estimated delivery time of the waybill;

[0040] The initial promised delivery time is compared with the estimated delivery time to determine whether there is a timeliness risk for the waybill.

[0041] A device for optimizing express delivery capacity, comprising:

[0042] A classification module is used to determine the trunk line capacity and branch line capacity according to the arrival site of each capacity;

[0043] A generation module, used to generate a data table of achievable time efficiency of trunk transport capacity and a data table of achievable time efficiency of branch transport capacity corresponding to the branch transport capacity according to the time efficiency of historical waybills;

[0044] A selection module is used to determine a time-saving data table from the branch line capacity achievable time-saving data table and the trunk line capacity achievable time-saving data table according to the destination city of the waybill when it is determined that the waybill has a time-saving risk;

[0045] A determination module is used to determine the optimal transportation capacity of the waybill according to the time-saving data table.

[0046] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above-mentioned methods for optimizing express delivery capacity when executing the computer program.

[0047] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the above-mentioned methods for optimizing express delivery capacity.

[0048] The above-mentioned method, device, computer equipment and storage medium for optimizing express delivery capacity first determine the trunk capacity and branch line capacity according to the arrival site, and then generate a trunk capacity achievable timeliness data table for the trunk capacity and a branch line capacity achievable timeliness data table corresponding to the branch line capacity according to the historical waybill timeliness; further, when it is determined that there is a timeliness risk in the waybill, a timeliness rescue data table is determined from the branch line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill, and the optimal capacity of the waybill is determined according to the timeliness rescue data table. This method generates achievable timeliness data tables for branch lines and trunk lines respectively by calculating the achievable timeliness, and can provide the optimal capacity for the waybill according to the achievable timeliness data table when there is a timeliness risk in the waybill, thereby ensuring that the delay risk of the waybill is reduced. Moreover, the achievable timeliness table is generated according to the historical waybill timeliness, so that the optimal capacity determined according to the achievable timeliness table is more objective, thereby improving accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is an application environment diagram of a method for optimizing express delivery capacity in one embodiment;

[0050] Figure 2 A schematic diagram of a flow chart of a method for optimizing express delivery capacity in one embodiment;

[0051] Figure 3 It is a flowchart of the steps of generating a data table of achievable time efficiency of trunk line capacity according to the time efficiency of historical waybills in one embodiment;

[0052] Figure 4 A flowchart of the steps of generating a branch line capacity achievable time efficiency data table corresponding to the branch line capacity according to the historical waybill time efficiency in one embodiment;

[0053] Figure 5 is a structural block diagram of a device for optimizing express delivery capacity in one embodiment;

[0054] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0055] 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.

[0056] The express delivery capacity optimization method provided in this application can be applied to Figure 1 In the application environment shown in FIG. 1 , the terminal 102 communicates with the server 104 through the network. After the terminal 102 receives the optimization instruction, the terminal 102 can independently implement the method for optimizing the express delivery capacity. The terminal 102 can also send the optimization instruction to the communicating server 104, and the server 104 implements the method for optimizing the express delivery capacity. After the server 104 determines the optimal capacity of the waybill, it returns it to the terminal 102 to inform the user.

[0057] Specifically, taking server 104 as an example, server 104 determines the trunk capacity and branch capacity according to the arrival site of each capacity; server 104 generates a trunk capacity achievable time data table for trunk capacity and a branch capacity achievable time data table corresponding to branch capacity according to the time of historical waybills; when server 104 determines that there is a time risk for the waybill, it determines a time-saving data table from the branch capacity achievable time data table and the trunk capacity achievable time data table according to the destination city of the waybill; and determines the optimal capacity of the waybill according to the time-saving data table. Among them, terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices, and server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0058] In one embodiment, Figure 2 As shown in FIG. 1 , a method for optimizing express delivery capacity is provided, and the method is applied to Figure 1 The server in the example is used to illustrate the following steps:

[0059] Step S202, determining the trunk line capacity and branch line capacity according to the arrival site of each capacity.

[0060] Among them, capacity usually refers to transportation force. The capacity in this embodiment can be understood as the various routes in logistics transportation. This embodiment prefers ten specific dimensions of capacity basic information to define capacity. The ten specific dimensions of capacity basic information are line code, line departure site, line arrival site, latest arrival time, latest arrival week, planned departure time, planned departure week, departure frequency, timeliness type, loading city / outlet (trunk capacity is loading city, branch line capacity is loading outlet). It should be understood that the preference of the above ten specific dimensions of capacity basic information does not mean that it is limited to this, and the capacity basic information can be increased and decreased accordingly according to the actual situation. For example, the capacity basic information can also include but is not limited to the line departure city, line destination city, line type, radiation outlets, etc.

[0061] The arrival site refers to the site arrived at by the line. The capacity when the arrival location is a network point is marked as branch line capacity, and the capacity when the arrival location is not a network point is marked as trunk line capacity.

[0062] Specifically, the server obtains the arrival sites of each transport capacity in the entire network, and marks each transport capacity as a trunk transport capacity or a branch transport capacity according to the arrival site of each transport capacity. For example, when the arrival site of the transport capacity is a network point, the transport capacity is marked as a branch transport capacity.

[0063] Step S204, generating a trunk line capacity achievable time efficiency data table for trunk line capacity and a branch line capacity achievable time efficiency data table corresponding to branch line capacity respectively according to the historical waybill time efficiency.

[0064] Among them, the historical waybill validity period refers to the waybill validity period of the historical waybills carried by each transport capacity for the corresponding loading city or loading outlet.

[0065] Specifically, after the trunk capacity and branch capacity are determined, the server obtains the historical waybills carried by the trunk capacity and branch capacity respectively. The trunk capacity obtains the historical waybills carried for the corresponding loading city, and the branch capacity obtains the historical waybills carried for the corresponding loading outlets. Then, the server obtains the waybill validity of each historical waybill respectively, and determines the achievable timeliness of the trunk capacity to the loading city, or determines the achievable timeliness of the branch capacity to the loading outlet according to the waybill validity of each historical waybill. Furthermore, the server generates a corresponding achievable timeliness data table based on the achievable timeliness of each capacity and the basic capacity information. The achievable timeliness of the trunk capacity to the loading city and the basic capacity information of the trunk capacity generate the trunk capacity achievable timeliness data table, and the achievable timeliness of the branch capacity to the loading outlet and the basic capacity information of the branch capacity generate the branch capacity achievable timeliness data table.

[0066] In addition, since the capacity arrangement is subject to change, in order to ensure the accuracy of the capacity availability data table, the capacity availability data table can be updated at a fixed time. Generally speaking, the capacity arrangement is roughly the same every week, so the capacity availability data table can be updated once a week.

[0067] Step S206, when it is determined that there is a timeliness risk in the waybill, a timeliness rescue data table is determined from the branch line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill.

[0068] The timeliness risk of a waybill means that the waybill may not be delivered within the initially promised delivery time. The timeliness saving data table is selected from the feeder capacity achievable timeliness data table and the trunk capacity achievable timeliness data table, and is used to determine the optimal capacity of the waybill to save the waybill and reduce the timeliness risk of the waybill.

[0069] Specifically, when a transit point receives a waybill corresponding to a shipment, the delivery risk of the shipment can be assessed. The server obtains the initial promised delivery time, and then determines whether the waybill currently has a timeliness risk based on the delivery time initially promised for the shipment. When it is determined that the waybill has a timeliness risk, a data table is selected from the feeder capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table as a timeliness rescue data table for rescuing the timeliness of the waybill based on the destination city of the waybill.

[0070] Step S208, determining the optimal transport capacity of the waybill according to the time-saving data table.

[0071] Specifically, after determining the time-saving data table of the waybill, the server first screens out the capacity that can be selected for the waybill according to the basic information of the capacity recorded in the time-saving data table, and obtains the optional capacity of the waybill. For example, when the time-saving data table corresponding to the waybill is the achievable time-saving data table of the trunk capacity, the optional trunk capacity that can be selected for the waybill is finally screened out. And when the time-saving data table corresponding to the waybill is the achievable time-saving data table of the branch capacity, the optional branch capacity that can be selected for the waybill is finally screened out. Then, the server obtains the achievable time corresponding to all optional capacities according to the achievable time recorded in the time-saving data table. All optional capacities are sorted according to the achievable time of the optional capacities, and the optional capacity with the fastest time is determined as the optimal capacity for the waybill.

[0072] The above-mentioned method for optimizing express delivery capacity first determines the trunk capacity and branch capacity according to the arrival site, and then generates the trunk capacity achievable time data table of the trunk capacity and the branch capacity achievable time data table corresponding to the branch capacity according to the historical waybill time; further, when it is determined that there is a time risk in the waybill, the time rescue data table is determined from the branch capacity achievable time data table and the trunk capacity achievable time data table according to the destination city of the waybill, and the optimal capacity of the waybill is determined according to the time rescue data table. This method generates achievable time data tables for branch lines and trunk lines respectively by calculating the achievable time, and can provide the optimal capacity for the waybill according to the achievable time data table when there is a time risk in the waybill, ensuring that the delay risk of the waybill is reduced. In addition, the achievable time table is generated based on the historical waybill time, so that the optimal capacity determined according to the achievable time table is more objective, thereby improving accuracy.

[0073] In one embodiment, Figure 3 As shown, a trunk line capacity achievable time efficiency data table of the trunk line capacity is generated according to the historical waybill time efficiency, including:

[0074] Step S302, obtaining each loading city corresponding to the trunk line capacity.

[0075] Among them, the loading city refers to the city carried by the trunk line capacity. For example, when line A is responsible for transporting express parcels from city A and city B, city A and city B are the loading cities of line A.

[0076] Specifically, the server obtains the loading data of the whole network capacity from the database, including but not limited to the line code of the capacity, the latest arrival time of the line, the timeliness type, the loading network point, the loading city, the loading area, etc. Then, the server selects the loading city corresponding to the trunk capacity from the loading data of the whole network capacity.

[0077] In addition, the whole network capacity also includes capacity vehicle logo data and waybill data. The capacity vehicle logo data includes but is not limited to vehicle logo number, line code, line departure site, line arrival site, planned departure time, planned arrival time, planned departure frequency, planned arrival frequency, vehicle logo and other data. Waybill data includes but is not limited to waybill number, vehicle logo number, timeliness type, operation site code, waybill departure city code, waybill departure site code, waybill destination city code, waybill destination site code, waybill destination district and county, waybill delivery time and other data. The capacity vehicle logo data is associated with the capacity loading data through the line code, and the capacity vehicle logo data is associated with the waybill data through the vehicle logo number.

[0078] Step S304, counting the historical waybill volume of each subordinate district and county of each loading city within the first preset time, and filtering out the remote districts and counties of each loading city to obtain the valid districts and counties of each loading city.

[0079] The districts and counties under the loading city refer to the districts and counties under the loading city. The number of historical waybills refers to the number of historical waybills. The first preset time is a preset time range, which can be configured according to actual needs.

[0080] Specifically, each city has multiple corresponding districts and counties, but for some cities, there are some remote districts and counties. On the one hand, the number of waybills arriving in these remote districts and counties is small, and the reference value is not great. On the other hand, the timeliness of waybills arriving in these remote districts and counties will be very long, which is an outlier and will have a certain impact on our timeliness calculation. Therefore, when calculating the timeliness that can be achieved by the trunk capacity, the influence of these remote districts and counties will be excluded. That is, the districts and counties under the loading city are first filtered, and those districts and counties whose historical waybills are less than a specific threshold are discarded, thereby excluding these remote districts and counties. By separately counting the historical waybills of each district and county under each loading city on the trunk capacity within the first preset time, the total historical waybills of each district and county under each loading city within the first preset time are obtained. Then, the historical waybills of each district and county under the preset first waybills threshold are compared respectively. The districts and counties with a historical waybills volume less than the first waybills threshold are screened out as remote districts and counties, and the remaining districts and counties are valid districts and counties. The first waybills threshold can be set according to actual needs.

[0081] Step S306, counting the historical waybill volume carried by the trunk line capacity for each valid district and county of each loading city within the second preset time, and determining the loading cities that can be covered by the trunk line capacity from among the loading cities.

[0082] The second preset time is a preset time range, which may be equal to the first preset time or may not be equal to the first preset time, and is configured according to actual needs.

[0083] Specifically, since the trunk transport capacity in this example is positioned in the city dimension, the trunk transport capacity is required to carry a certain number of historical waybills for the loading city within a specific time. In addition, the trunk transport capacity is also required to be able to reach every district and county under the loading city. Therefore, the historical waybill volume carried by the trunk transport capacity for each valid district and county of each loading city within the second preset time is counted. If the historical waybill volume carried by the trunk transport capacity for the valid district and county under the corresponding loading city exceeds the preset second waybill volume threshold, it means that the trunk transport capacity can cover the valid district and county. Furthermore, when the trunk transport capacity can cover all valid districts and counties under the loading city, it means that the trunk transport capacity can cover the loading city, and the loading city is a loading city that can be covered by the trunk transport capacity. The second waybill volume threshold can be set according to actual needs.

[0084] Step S308, obtaining the planned dispatch time of the trunk transport capacity, and separately counting the historical waybills of the trunk transport capacity for each covered loading city.

[0085] Specifically, the server obtains the planned dispatch time of the trunk transport capacity from the time-saving data table. At the same time, the historical waybill time of the historical waybills carried by the trunk transport capacity for each covered loading city is counted separately, that is, the waybill time of the historical waybills carried by the trunk transport capacity to each covered loading city is counted separately. For example, the covered loading cities include City 1 and City 2, that is, the waybill time of the historical waybills carried by the trunk transport capacity to City 1 is counted, and the waybill time of the historical waybills carried by the trunk transport capacity to City 2 is counted.

[0086] Step S310, based on the historical waybill time and planned departure time of each covered loading city, the achievable time for the trunk line capacity to reach each covered loading city is calculated respectively.

[0087] Specifically, since each waybill has a corresponding time limit, and most waybill can usually be delivered on time, it can be determined that 80% of the waybill can be delivered on time based on the time limits of historical waybill. Therefore, the time limit corresponding to the 80th percentile of the historical waybill time limits corresponding to each loading city is obtained, which is called the 80th percentile time limit. Then, the difference between the 80th percentile time limit and the planned dispatch time of the trunk capacity is calculated to obtain the achievable time limit for the trunk capacity to reach the covered loading city. After statistics, the achievable time limits can finally be classified into the following eight achievable time limit types, and their codes and meanings are as follows:

[0088] 1D12: Available before 12:00 on the same day;

[0089] 1D18: Available before 18:00 on the same day;

[0090] 1D24: available before 24:00 on the same day;

[0091] 2D12: Available before 12:00 the next day;

[0092] 2D18: Available before 18:00 the next day;

[0093] 2D24: available before 24:00 the next day;

[0094] 3D12: can be reached before 12:00 the day after tomorrow;

[0095] 3D18: Available before 18:00 the day after tomorrow;

[0096] 3D24: Available before 24:00 the day after tomorrow;

[0097] 4D and above: can be reached in more than three days.

[0098] Step S312, generating a data table of achievable time efficiency of trunk line capacity according to the basic capacity information of trunk line capacity and the achievable time efficiency of reaching each covered loading city.

[0099] Specifically, after calculating the achievable time for the trunk line capacity to reach the covered loading cities, the achievable time and the basic capacity information corresponding to the trunk line capacity can be combined into a data table to obtain a data table of achievable time for the trunk line capacity.

[0100] In this embodiment, the abnormal counties and cities are screened out through the historical waybill volume to obtain the covered cities, and then the achievable time to reach the covered cities is calculated, which can ensure accuracy. At the same time, the achievable time calculated based on the time of historical waybills is more accurate.

[0101] In one embodiment, Figure 4 As shown in the figure, generating a branch line capacity achievable time efficiency data table corresponding to the branch line capacity according to the historical waybill time efficiency includes the following steps:

[0102] Step S402, obtaining each loading point corresponding to the branch line capacity.

[0103] Among them, the loading points refer to the points included in the branch line capacity. For example, when the points undertaken by line A include point A and point B, point A and point B are the loading points of line A.

[0104] Specifically, the server obtains the loading data of the whole network capacity from the database, including but not limited to the line code of the capacity, the latest arrival time of the line, the timeliness type, the loading network point, the loading city, the loading area, etc. Then, the server selects the loading network point corresponding to the branch line capacity from the loading data of the whole network capacity.

[0105] Step S404, respectively counting the historical waybills of the branch line transport capacity for each loading outlet, and obtaining the planned dispatching time of the branch line transport capacity.

[0106] Specifically, since the number of waybills for branch line capacity is less than that for trunk line capacity, and branch line capacity directly reaches the destination outlets, the achievable time efficiency of branch line capacity is based on the outlet dimension. Therefore, there is no need to consider the county coverage and city coverage of capacity as when calculating the achievable time efficiency of trunk line capacity. The achievable time efficiency of branch line capacity can be directly calculated based on the historical carrying waybills of branch line capacity and the loading outlets of branch line capacity. That is, after the server determines the loading outlets of the linear capacity, it separately counts the historical waybill time efficiency of the historical waybills carried by the branch line capacity for each loading outlet, that is, it separately counts the waybill time efficiency of the historical waybills carried by the branch line capacity and arriving at each loading outlet. At the same time, the server obtains the planned dispatch time of the trunk line capacity from the time efficiency rescue data table.

[0107] Step S406, calculate the difference between the 80th percentile of the historical waybill time efficiency corresponding to each loading network point and the planned departure time, and obtain the achievable time efficiency of the branch line capacity to reach each loading network point.

[0108] Specifically, the calculation principle of trunk line capacity is the same as that of the 80th percentile of the historical waybill time efficiency corresponding to each loading outlet of the branch line capacity, which is called the 80th percentile time efficiency. Then, the difference between the 80th percentile time efficiency and the planned dispatch time of the branch line capacity is calculated to obtain the achievable time efficiency for the branch line capacity to arrive at the loading city outlet.

[0109] Step S408, generating a data table of achievable time efficiency of branch line capacity according to the basic information of branch line capacity and the achievable time efficiency of reaching each loading network point.

[0110] Specifically, after calculating the achievable time for the branch line capacity to reach the covered loading cities, the achievable time and the basic capacity information corresponding to the branch line capacity can be combined into a data table to obtain a data table of achievable time for branch line capacity.

[0111] In this embodiment, the achievable time efficiency is calculated based on the time efficiency of the branch line capacity corresponding to the historical waybills, so that a more accurate time efficiency can be obtained, thereby improving the accuracy of the optimal capacity.

[0112] In one embodiment, step S206 includes: when it is determined that there is a time risk for the waybill, obtaining the city of the current transfer station of the waybill and the destination city of the waybill; when the city of the current transfer station and the destination city are consistent, determining the time data table that can be achieved by the branch line capacity as a time-saving data table; when the city of the current transfer station and the destination city are inconsistent, determining the time data table that can be achieved by the trunk line capacity as a time-saving data table.

[0113] Specifically, when it is determined that there is a time risk for the waybill, the server determines the destination city of the waybill based on the waybill information corresponding to the waybill, that is, the city to which the waybill is finally delivered. At the same time, the city of the transit yard where the waybill is currently located is determined based on the transit yard that currently receives the waybill. Then, the city of the current transit yard is compared with the destination city to determine whether the two are consistent. If they are consistent, it means that the express corresponding to the waybill has been delivered to the destination city. At this time, the express corresponding to the waybill does not need to be transported between cities, so the branch line capacity can achieve time data table with outlets as the dimension is selected as the time-saving data table. If they are inconsistent, it means that the express corresponding to the waybill has not yet been delivered to the final destination city, and subsequent transportation still needs to be carried out between cities. Therefore, the trunk line capacity can achieve time data table with cities as the dimension is selected as the time-saving data table.

[0114] In this embodiment, the selected time-saving data table is determined by the destination city and the current city of the waybill, so as to ensure the accuracy of the transport capacity selection.

[0115] In one embodiment, when the time-saving data table is a branch line capacity achievable time-effectiveness data table, step S208 includes: based on the branch line capacity achievable time-effectiveness data table, screening out candidate branch line capacities including the destination outlets of the waybill; obtaining the latest arrival time of each candidate branch line capacity and the arrival time of the waybill at the current transfer yard; screening candidate branch line capacities whose latest arrival time is after the arrival time to obtain optional branch line capacities; obtaining the achievable time-effectiveness of the optional branch line capacities, comparing the achievable time-effectiveness of each optional branch line capacity, and determining the optional branch line capacity with the fastest time-effectiveness as the optimal capacity for the waybill.

[0116] Among them, the candidate branch line capacity refers to the branch line capacity that includes the corresponding destination outlets, and the optional branch line capacity refers to the branch line capacity that can be selected as the carrying capacity from the candidate branch line capacity.

[0117] Specifically, since the branch line capacity achievable time data table records the loading outlets included in each branch line capacity. Therefore, the server determines the destination outlet of the waybill based on the waybill information of the waybill. Then, each branch line capacity is screened according to the outlets included in each branch line capacity, and the branch line capacity including the destination outlet of the waybill is screened out to obtain the candidate branch line capacity. For example, when the destination outlet of the waybill is outlet A, all branch line capacities including outlet A are screened out to obtain the candidate branch line capacity. At the same time, the latest arrival time of the line corresponding to each candidate branch line capacity is obtained from the branch line capacity achievable time data table. In addition, the arrival time of the waybill at the current transfer yard is obtained. For example, the time when the transfer yard receives the express corresponding to the waybill, or the scanning time when the waybill is scanned can be used as the arrival time at the transfer yard.

[0118] Then, since the latest arrival time of the line indicates the latest time that the line arrives at the transfer yard, if the time when the express corresponding to the waybill arrives at the transfer yard is later than the latest arrival time of the line, it means that the express cannot be sent to the next transfer yard with the branch line capacity. Therefore, the server selects the candidate branch line capacity whose latest arrival time is after the arrival time to obtain the optional branch line capacity. In order to obtain the fastest optimal capacity, the achievable time of all optional branch line capacities is obtained from the branch line capacity achievable time data table. Sort them according to the order of achievable time, and select the optional branch line capacity with the fastest time as the optimal capacity. The screening process can be expressed as follows: assuming that the branch line capacity includes branch line capacity A, B, C, D, and E, the screened candidate branch line capacity includes branch line capacity A, C, D, and E, and the optional branch line capacity screened from the candidate branch line capacity includes branch line capacity A, C, and D. After sorting by achievable time efficiency, the optimal capacity is one of A, C, and D, and the remaining two are alternative capacities.

[0119] In this embodiment, screening is performed step by step based on the destination network, time and timeliness, and the optimal transportation capacity is finally determined, which can not only ensure the accuracy of the optimal transportation capacity but also ensure the availability of the optimal transportation capacity.

[0120] In one embodiment, when the time-saving data table is a trunk capacity achievable time-effectiveness data table, step S208 includes: obtaining the arrival time of the waybill at the current transfer yard; based on the trunk capacity achievable time-effectiveness data table, screening out a first candidate trunk capacity whose loading city includes the destination city of the waybill but the destination city is different from the destination city of the waybill; for the trunk capacity whose destination city is the same as the destination city of the waybill, screening the trunk capacity of the destination transfer yard including the destination outlet of the waybill to obtain a second candidate trunk capacity; respectively obtaining the latest arrival time of the first candidate trunk capacity and the second candidate trunk capacity; screening the candidate trunk capacity whose latest arrival time is after the arrival time from the first candidate trunk capacity and the second candidate trunk capacity to obtain an optional trunk capacity; obtaining the achievable time of each optional trunk capacity, comparing the achievable time of each optional trunk capacity, and determining the optional trunk capacity with the fastest time-effectiveness as the optimal capacity of the waybill.

[0121] The first candidate trunk capacity is the trunk capacity that contains the destination city of the waybill but its own destination city is different from the destination city of the waybill. The second candidate trunk capacity is the trunk capacity that meets the following three conditions: the destination city of the waybill, its own destination city is the same as the destination city of the waybill, and its own destination transfer station contains the destination outlet of the waybill. The optional branch capacity refers to the trunk capacity that can be selected as the carrying capacity from the first candidate trunk capacity and the second candidate trunk capacity.

[0122] Specifically, since the trunk capacity can be achieved in the time-effectiveness data table, the loading cities included in each trunk capacity are recorded. Therefore, the server determines the destination city of the waybill based on the waybill information of the waybill. Then, each trunk capacity is screened according to the loading cities included in each trunk capacity, and the trunk capacity including the destination city of the waybill is screened out to obtain the candidate trunk capacity. Among them, the trunk capacity that only includes the destination city of the waybill in the candidate trunk capacity but its own destination city is different from the destination city of the waybill is the first candidate trunk capacity. And the remaining candidate trunk capacities excluding the first candidate trunk capacity are further screened out from the destination transfer yard including the trunk capacity of the destination outlet corresponding to the waybill to obtain the second candidate trunk capacity.

[0123] Then, similarly, since the latest arrival time of the line indicates the latest time that the line arrives at the transfer yard, if the express delivery corresponding to the waybill arrives at the transfer yard later than the latest arrival time of the line, it means that the express delivery cannot be sent to the next transfer yard with the branch line capacity. Therefore, the server selects the candidate branch line capacity whose latest arrival time is after the arrival time from the first candidate trunk line capacity and the second candidate trunk line capacity to obtain the optional trunk line capacity. In order to obtain the fastest optimal capacity, the achievable time of all optional trunk capacity is obtained from the trunk capacity achievable time data table. Sort them according to the order of achievable time, and select the optional trunk line capacity with the fastest time as the optimal capacity.

[0124] In this embodiment, screening is performed step by step based on cities, outlets, time and time efficiency, and the optimal transport capacity is finally determined, which can not only ensure the accuracy of the optimal transport capacity but also ensure the availability of the optimal transport capacity.

[0125] In one embodiment, a method for determining whether a waybill has a time risk includes: obtaining an initial promised delivery time and an estimated delivery time of the waybill; and comparing the initial promised delivery time with the estimated delivery time to determine whether the waybill has a time risk.

[0126] The initial promised delivery time refers to the delivery time promised to the sender when sending the package, and the expected delivery time is the current dynamic estimated delivery time. The expected delivery time can be understood as the estimated transportation time between the current location and the final delivery point.

[0127] Specifically, when determining whether the express shipment corresponding to the waybill has a time-limit risk, the initial promised delivery time is obtained. At the same time, the expected delivery time is dynamically estimated. Then, the initial promised delivery time is compared with the expected delivery time. When the initial promised delivery time is after the expected delivery time, it means that the express shipment can be delivered on time and there is no time-limit risk. When the initial promised delivery time is before the expected delivery time, it means that there is a risk that the express shipment cannot be delivered on time and there is a time-limit risk.

[0128] In this embodiment, by comparing the dynamically estimated expected delivery time with the initially promised delivery time, the accuracy of determining whether there is a timeliness risk can be improved.

[0129] It should be understood that although Figure 2-4 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-4 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0130] In one embodiment, Figure 5 As shown, a device for optimizing express delivery capacity is provided, including: a classification module 502, a generation module 504, a selection module 506 and a determination module 508, wherein:

[0131] A classification module 502, for determining the trunk line capacity and the branch line capacity according to the arrival site of each capacity;

[0132] A generating module 504, for generating a trunk line capacity achievable time efficiency data table for trunk line capacity and a branch line capacity achievable time efficiency data table corresponding to branch line capacity according to the historical waybill time efficiency;

[0133] A selection module 506 is used to determine a time-saving data table from the branch line capacity achievable time-saving data table and the trunk line capacity achievable time-saving data table according to the destination city of the waybill when it is determined that the waybill has a time-saving risk;

[0134] The determination module 508 is used to determine the optimal transportation capacity of the waybill according to the time-saving data table.

[0135] In one embodiment, the generation module 504 is also used to obtain each loading city corresponding to the trunk transport capacity; count the historical waybill volume of each subordinate district and county of each loading city within the first preset time, screen out the remote districts and counties of each loading city, and obtain the effective districts and counties of each loading city; count the historical waybill volume carried by the trunk transport capacity for each effective district and county of each loading city within the second preset time, and determine the loading cities that can be covered by the trunk transport capacity from each loading city; obtain the planned dispatch time of the trunk transport capacity, and count the historical waybill timeliness of the historical waybills carried by the trunk transport capacity for each coverable loading city; calculate the achievable timeliness of the trunk transport capacity to reach each coverable loading city according to the historical waybill timeliness and planned departure time of each coverable loading city; generate a trunk transport capacity achievable timeliness data table according to the basic capacity information of the trunk transport capacity and the achievable timeliness to reach each coverable loading city.

[0136] In one embodiment, the generation module 504 is also used to obtain each loading point corresponding to the branch line capacity; respectively count the historical waybill time of the historical waybills carried by the branch line capacity for each loading point, and obtain the planned dispatch time of the branch line capacity; calculate the difference between the 80th percentile of the historical waybill time corresponding to each loading point and the planned departure time, and obtain the achievable time of the branch line capacity to arrive at each of the loading points; generate a branch line capacity achievable time data table based on the basic capacity information of the branch line capacity and the achievable time to arrive at each of the loading points.

[0137] In one embodiment, the selection module 506 is also used to obtain the city of the current transfer station of the waybill and the destination city of the waybill when it is determined that there is a time risk in the waybill; when the city of the current transfer station and the destination city are consistent, determine the time data table that can be achieved by the branch line capacity as a time-saving data table; when the city of the current transfer station and the destination city are inconsistent, determine the time data table that can be achieved by the trunk line capacity as a time-saving data table.

[0138] In one embodiment, the determination module 508 is also used to screen out candidate branch line capacities including the destination outlets of the waybill based on the data table of achievable timeliness of branch line capacities; obtain the latest arrival time of each candidate branch line capacity and the arrival time of the waybill at the current transfer yard; screen out candidate branch line capacities whose latest arrival time is after the arrival time to obtain optional branch line capacities; obtain the achievable timeliness of the optional branch line capacities, compare the achievable timeliness of each optional branch line capacity, and determine the optional branch line capacity with the fastest timeliness as the optimal capacity for the waybill.

[0139] In one embodiment, the determination module 508 is also used to obtain the arrival time of the waybill at the current transfer yard; according to the data table of achievable timeliness of trunk capacity, screen out the first candidate trunk capacity whose loading city includes the destination city of the waybill but the destination city is different from the destination city of the waybill; for the trunk capacity whose destination city is the same as the destination city of the waybill, screen the trunk capacity of the destination transfer yard including the destination outlet of the waybill to obtain the second candidate trunk capacity; obtain the latest arrival time of the first candidate trunk capacity and the second candidate trunk capacity respectively; screen the candidate trunk capacity whose latest arrival time of the route is after the arrival time from the first candidate trunk capacity and the second candidate trunk capacity to obtain the optional trunk capacity; obtain the achievable timeliness of each optional trunk capacity, compare the achievable timeliness of each optional trunk capacity, and determine the optional trunk capacity with the fastest timeliness as the optimal capacity of the waybill.

[0140] In one embodiment, the selection module 506 is also used to obtain the initial promised delivery time and the estimated delivery time of the waybill; compare the initial promised delivery time with the estimated delivery time to determine whether there is a timeliness risk for the waybill.

[0141] For the specific definition of the express delivery capacity optimization device, please refer to the definition of the express delivery capacity optimization method above, which will not be repeated here. The various modules in the above-mentioned express delivery capacity optimization device can be implemented in whole or in part through software, hardware and their combination. 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.

[0142] 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 capacity loading data, capacity vehicle logo data, waybill data, etc. 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 optimizing express delivery capacity is implemented.

[0143] 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.

[0144] 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:

[0145] Determine trunk line capacity and branch line capacity based on the arrival location of each capacity;

[0146] Generate a data table of achievable time efficiency of trunk line capacity and a data table of achievable time efficiency of branch line capacity corresponding to branch line capacity according to the time efficiency of historical waybills;

[0147] When it is determined that there is a timeliness risk in the waybill, the timeliness saving data table is determined from the feeder line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill;

[0148] Determine the optimal transport capacity for the waybill based on the time-saving data table.

[0149] In one embodiment, the processor also implements the following steps when executing the computer program: obtaining each loading city corresponding to the trunk transport capacity; counting the historical waybill volume of each subordinate district and county of each loading city within the first preset time, and filtering out the remote districts and counties of each loading city to obtain the effective districts and counties of each loading city; counting the historical waybill volume carried by the trunk transport capacity for each effective district and county of each loading city within the second preset time, and determining the loading cities that can be covered by the trunk transport capacity from each loading city; obtaining the planned dispatch time of the trunk transport capacity, and counting the historical waybill timeliness of the historical waybills carried by the trunk transport capacity for each coverable loading city; calculating the achievable timeliness of the trunk transport capacity to arrive at each coverable loading city according to the historical waybill timeliness and planned departure time of each coverable loading city; generating a trunk transport capacity achievable timeliness data table according to the basic capacity information of the trunk transport capacity and the achievable timeliness to arrive at each coverable loading city.

[0150] In one embodiment, the processor further implements the following steps when executing the computer program: obtaining each loading point corresponding to the branch line capacity; respectively counting the historical waybill time of the historical waybills carried by the branch line capacity for each loading point, and obtaining the planned dispatch time of the branch line capacity; calculating the difference between the 80th percentile of the historical waybill time corresponding to each loading point and the planned departure time, and obtaining the achievable time of the branch line capacity to arrive at each of the loading points; generating a data table of achievable time of the branch line capacity according to the basic capacity information of the branch line capacity and the achievable time to arrive at each of the loading points.

[0151] In one embodiment, the processor also implements the following steps when executing the computer program: when it is determined that there is a time risk for the waybill, the city of the current transfer station of the waybill and the destination city of the waybill are obtained; when the city of the current transfer station and the destination city are consistent, the time data table of the branch line capacity that can be achieved is determined as a time-saving data table; when the city of the current transfer station and the destination city are inconsistent, the time data table of the trunk line capacity that can be achieved is determined as a time-saving data table.

[0152] In one embodiment, the processor also implements the following steps when executing the computer program: based on the branch line capacity achievable time data table, filter out candidate branch line capacities that include the destination outlets of the waybill; obtain the latest arrival time of each candidate branch line capacity and the arrival time of the waybill at the current transfer station; filter out candidate branch line capacities whose latest arrival time is after the arrival time to obtain optional branch line capacities; obtain the achievable time of the optional branch line capacities, compare the achievable time of each optional branch line capacity, and determine the optional branch line capacity with the fastest time as the optimal capacity for the waybill.

[0153] In one embodiment, the processor also implements the following steps when executing the computer program: obtaining the arrival time of the waybill at the current transfer yard; screening out the first candidate trunk capacity whose loading city includes the destination city of the waybill but the destination city is different from the destination city of the waybill according to the achievable time efficiency data table of the trunk capacity; for the trunk capacity whose destination city is the same as the destination city of the waybill, screening the trunk capacity of the destination transfer yard including the destination outlet of the waybill to obtain the second candidate trunk capacity; obtaining the latest arrival time of the first candidate trunk capacity and the second candidate trunk capacity respectively; screening the candidate trunk capacity whose latest arrival time of the route is after the arrival time from the first candidate trunk capacity and the second candidate trunk capacity to obtain the optional trunk capacity; obtaining the achievable time efficiency of each optional trunk capacity, comparing the achievable time efficiency of each optional trunk capacity, and determining the optional trunk capacity with the fastest time efficiency as the optimal capacity of the waybill.

[0154] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the initial promised delivery time and the expected delivery time of the waybill; comparing the initial promised delivery time with the expected delivery time to determine whether there is a time risk for the waybill.

[0155] 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:

[0156] Determine trunk line capacity and branch line capacity based on the arrival location of each capacity;

[0157] Generate a data table of achievable time efficiency of trunk line capacity and a data table of achievable time efficiency of branch line capacity corresponding to branch line capacity according to the time efficiency of historical waybills;

[0158] When it is determined that there is a timeliness risk in the waybill, the timeliness saving data table is determined from the feeder line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill;

[0159] Determine the optimal transport capacity for the waybill based on the time-saving data table.

[0160] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining each loading city corresponding to the trunk transport capacity; counting the historical waybill volume of each subordinate district and county of each loading city within the first preset time, and filtering out the remote districts and counties of each loading city to obtain the effective districts and counties of each loading city; counting the historical waybill volume carried by the trunk transport capacity for each effective district and county of each loading city within the second preset time, and determining the loading cities that can be covered by the trunk transport capacity from each loading city; obtaining the planned dispatch time of the trunk transport capacity, and counting the historical waybill timeliness of the historical waybills carried by the trunk transport capacity for each coverable loading city; calculating the achievable timeliness of the trunk transport capacity to reach each coverable loading city based on the historical waybill timeliness and planned departure time of each coverable loading city; generating a data table of achievable timeliness of the trunk transport capacity based on the basic capacity information of the trunk transport capacity and the achievable timeliness to reach each coverable loading city.

[0161] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining each loading outlet corresponding to the branch line capacity; respectively counting the historical waybill time of the historical waybills carried by the branch line capacity for each loading outlet, and obtaining the planned dispatch time of the branch line capacity; calculating the difference between the 80th percentile of the historical waybill time corresponding to each loading outlet and the planned departure time, and obtaining the achievable time of the branch line capacity to arrive at each of the loading outlets; generating a data table of the achievable time of the branch line capacity based on the basic capacity information of the branch line capacity and the achievable time to arrive at each of the loading outlets.

[0162] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when it is determined that there is a time risk for the waybill, the city of the current transfer station of the waybill and the destination city of the waybill are obtained; when the city of the current transfer station and the destination city are consistent, the time data table of the branch line capacity that can be achieved is determined as a time-saving data table; when the city of the current transfer station and the destination city are inconsistent, the time data table of the trunk line capacity that can be achieved is determined as a time-saving data table.

[0163] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the data table of achievable timeliness of branch line capacity, candidate branch line capacities including the destination outlets of the waybill are screened out; the latest arrival time of each candidate branch line capacity and the arrival time of the waybill at the current transfer yard are obtained; candidate branch line capacities whose latest arrival time is after the arrival time are screened to obtain optional branch line capacities; the achievable timeliness of the optional branch line capacities is obtained, the achievable timeliness of each optional branch line capacity is compared, and the optional branch line capacity with the fastest timeliness is determined as the optimal capacity for the waybill.

[0164] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the arrival time of the waybill at the current transfer yard; based on the achievable time data table of the trunk capacity, screening out the first candidate trunk capacity whose loading city includes the destination city of the waybill but the destination city is different from the destination city of the waybill; for the trunk capacity whose destination city is the same as the destination city of the waybill, screening the trunk capacity of the destination transfer yard including the destination outlet of the waybill to obtain the second candidate trunk capacity; obtaining the latest arrival time of the first candidate trunk capacity and the second candidate trunk capacity respectively; screening the candidate trunk capacity whose latest arrival time of the route is after the arrival time from the first candidate trunk capacity and the second candidate trunk capacity to obtain the optional trunk capacity; obtaining the achievable time of each optional trunk capacity, comparing the achievable time of each optional trunk capacity, and determining the optional trunk capacity with the fastest time as the optimal capacity of the waybill.

[0165] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the initial promised delivery time and the estimated delivery time of the waybill; comparing the initial promised delivery time with the estimated delivery time to determine whether there is a time risk for the waybill.

[0166] 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 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).

[0167] The technical features of the above embodiments may be arbitrarily combined. 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.

[0168] The above-mentioned 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 optimizing express delivery capacity, characterized in that: The method comprises: Determine trunk and branch line capacity based on the arrival sites of each capacity; Obtaining each loading city corresponding to the trunk line capacity and each loading outlet corresponding to the branch line capacity; Count the historical waybill volumes of each district and county under each loading city within the first preset time, and filter out the remote districts and counties of each loading city to obtain the valid districts and counties of each loading city; Counting the historical waybill volume carried by the trunk line transport capacity for each of the valid counties of each of the loading cities within the second preset time, and determining the loading cities that can be covered by the trunk line transport capacity from each of the loading cities; Obtaining the planned dispatch time of the trunk transport capacity, and respectively counting the historical waybills of the trunk transport capacity for each of the covered loading cities; According to the historical waybill validity of each of the covered loading cities and the planned dispatching time, respectively calculate the achievable validity of the trunk line capacity to arrive at each of the covered loading cities; Generate a data table of achievable time efficiency of trunk line capacity according to the basic information of trunk line capacity and the achievable time efficiency of reaching each of the coverable loading cities; Respectively count the historical waybills of the branch line transport capacity for each of the loading outlets, and obtain the planned dispatch time of the branch line transport capacity; Calculate the difference between the percentile of the historical waybill time efficiency corresponding to each of the distribution network points and the planned dispatch time to obtain the achievable time efficiency of the branch line capacity to reach each of the distribution network points; the percentile is determined based on the time efficiency of on-time delivery in the historical waybill time efficiency; Generate a data table of achievable time efficiency of branch line transport capacity according to the basic transport capacity information of the branch line transport capacity and the achievable time efficiency of reaching each of the loading outlets; When it is determined that there is a timeliness risk in the waybill, a timeliness saving data table is determined from the feeder line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill; The optimal transport capacity of the waybill is determined according to the time-saving data table.

2. The method according to claim 1, characterized in that: The percentile is the 80th percentile of the historical waybill time efficiency.

3. The method according to claim 1, characterized in that When it is determined that there is a timeliness risk in the waybill, a timeliness saving data table is determined from the branch line capacity achievable timeliness data table and the trunk line capacity achievable timeliness data table according to the destination city of the waybill, including: When it is determined that there is a timeliness risk in the waybill, the city where the waybill is currently located and the destination city of the waybill are obtained; When the current transfer station city is consistent with the destination city, determining the branch line capacity achievable time efficiency data table as the time efficiency saving data table; When the city of the current transfer station is inconsistent with the destination city, the trunk line capacity achievable time data table is determined as the time saving data table.

4. The method according to claim 1, characterized in that: When the time-saving data table is a branch line capacity achievable time-saving data table, determining the optimal capacity of the waybill according to the time-saving data table includes: Based on the feeder transport capacity achievable time data table, select candidate feeder transport capacity including the destination network point of the waybill; Obtain the latest arrival time of each candidate branch line capacity and the arrival time of the waybill at the current transfer yard; Filter candidate branch line transport capacity whose latest arrival time of the line is after the arrival time to obtain optional branch line transport capacity; The achievable time of the optional branch line transport capacity is obtained, the achievable time of each optional branch line transport capacity is compared, and the optional branch line transport capacity with the fastest time is determined as the optimal transport capacity of the waybill.

5. The method according to claim 1, characterized in that When the time-saving data table is a trunk line capacity achievable time-saving data table, determining the optimal capacity of the waybill according to the time-saving data table includes: Obtain the arrival time of the waybill at the current transfer station; According to the achievable time efficiency data table of trunk transport capacity, a first candidate trunk transport capacity is selected where the loading city includes the destination city of the waybill but the destination city is different from the destination city of the waybill; For trunk transport capacity with the same destination city as the destination city of the waybill, the trunk transport capacity of the destination transfer station including the destination outlet of the waybill is screened to obtain the second candidate trunk transport capacity; Obtain the latest arrival time of the first candidate trunk line capacity and the second candidate trunk line capacity respectively; Select the candidate trunk line capacity whose latest arrival time of the route is after the arrival time from the first candidate trunk line capacity and the second candidate trunk line capacity to obtain the optional trunk line capacity; Obtain the achievable time of each of the optional trunk transport capacities, compare the achievable time of each of the optional trunk transport capacities, and determine the optional trunk transport capacity with the fastest time as the optimal transport capacity for the waybill.

6. The method according to claim 1 or 3, characterized in that: The method for determining that the waybill has a timeliness risk comprises: Get the initial promised delivery time and estimated delivery time of the waybill; The initial promised delivery time is compared with the estimated delivery time to determine whether there is a timeliness risk for the waybill.

7. A device for optimizing express delivery capacity, characterized in that: The device comprises: A classification module is used to determine the trunk line capacity and branch line capacity according to the arrival site of each capacity; A generation module is used to obtain each loading city corresponding to the trunk transport capacity and each loading outlet corresponding to the branch transport capacity; count the historical waybill volume of each subordinate district and county of each loading city within a first preset time, and screen out the remote districts and counties of each loading city to obtain the effective districts and counties of each loading city; count the historical waybill volume carried by the trunk transport capacity for each effective district and county of each loading city within a second preset time, and determine the loading cities that can be covered by the trunk transport capacity from each loading city; obtain the planned dispatch time of the trunk transport capacity, and count the historical waybill validity of the historical waybill carried by the trunk transport capacity for each covered loading city; calculate the historical waybill validity of each covered loading city and the planned dispatch time respectively. The achievable time for the trunk transport capacity to arrive at each of the covered loading cities; generate a data table of the achievable time for the trunk transport capacity based on the basic capacity information of the trunk transport capacity and the achievable time for arriving at each of the covered loading cities; respectively count the historical waybill time of the historical waybills carried by the branch transport capacity for each of the loading outlets, and obtain the planned dispatch time of the branch transport capacity; calculate the difference between the quantile of the historical waybill time corresponding to each of the loading outlets and the planned dispatch time, and obtain the achievable time for the branch transport capacity to arrive at each of the loading outlets; the quantile is determined based on the time for on-time delivery in the historical waybill time; generate a data table of the achievable time for the branch transport capacity based on the basic capacity information of the branch transport capacity and the achievable time for arriving at each of the loading outlets; A selection module is used to determine a time-saving data table from the branch line capacity achievable time-saving data table and the trunk line capacity achievable time-saving data table according to the destination city of the waybill when it is determined that the waybill has a time-saving risk; A determination module is used to determine the optimal transportation capacity of the waybill according to the time-saving data table.

8. The device according to claim 7, characterized in that The selection module is also used for: when it is determined that there is a time risk in the waybill, obtaining the city of the current transfer station of the waybill and the destination city of the waybill; when the city of the current transfer station and the destination city are consistent, determining the time data table that the branch line capacity can achieve as a time-saving data table; when the city of the current transfer station and the destination city are inconsistent, determining the time data table that the trunk line capacity can achieve as a time-saving data table.

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 6 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 6 are implemented.

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