E-commerce logistics management system and method based on big data

Abstract

The invention discloses an e-commerce logistics management system and method based on big data, and the method comprises the steps: obtaining logistics vehicle information and a plurality of e-commerce logistics demands in a preset period, and enabling the e-commerce logistics demands to comprise an article attribute, a shipping address, and a receiving address; determining a plurality of logistics schemes based on the article attributes in the plurality of e-commerce logistics demands; each logistics scheme comprises a plurality of logistics vehicles, and the model and the transportation task of each logistics vehicle; the transportation task comprises a shipping address, a receiving address and a loading amount corresponding to at least one e-commerce logistics demand; based on the current logistics vehicle information and a preset constraint condition, determining a target logistics scheme and a plurality of target logistics vehicles in the plurality of logistics schemes; and associating the plurality of transportation tasks in the target logistics scheme with the plurality of target logistics vehicles in a one-to-one correspondence manner, and sending the transportation tasks to the corresponding target logistics vehicles. The technical problems that in the prior art, e-commerce logistics management is low in efficiency and prone to errors are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce logistics management, and in particular to an e-commerce logistics management system and method based on big data. Background Art

[0002] With the rapid development of e-commerce, more goods need to be transported to consumers through logistics. The rapid increase in the number of goods has brought difficulties to the management of logistics.

[0003] In the prior art, logistics data is usually managed manually and the transportation of goods is arranged manually, but manual management has problems such as low efficiency and prone to errors.

[0004] It can be seen that in the process of e-commerce logistics management, how to improve efficiency and accuracy is an urgent problem to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide an e-commerce logistics management system and method based on big data, which solves the technical problems of low efficiency and easy errors in e-commerce logistics management in the prior art.

[0006] In a first aspect, the present invention provides an e-commerce logistics management method based on big data, the management method comprising:

[0007] Obtaining logistics vehicle information and multiple e-commerce logistics requirements within a preset period, wherein the e-commerce logistics requirements include item attributes, shipping address, and receiving address; item attributes include item name, volume, and weight;

[0008] Based on the attributes of items in multiple e-commerce logistics requirements, several logistics plans are determined; each logistics plan includes several logistics vehicles, as well as the model and transportation task of each logistics vehicle; the transportation task includes at least one shipping address, receiving address and loading quantity corresponding to the e-commerce logistics requirement;

[0009] Based on the current logistics vehicle information and preset constraints, confirm the target logistics plan and several target logistics vehicles among several logistics plans;

[0010] Several transportation tasks in the target logistics plan are associated with several target logistics vehicles one by one, and sent to the corresponding target logistics vehicles.

[0011] Furthermore, based on the attributes of items in multiple e-commerce logistics requirements, several logistics solutions are confirmed, including:

[0012] Obtain logistics solution model;

[0013] The attributes of items in multiple e-commerce logistics demands are input into the logistics solution model to obtain several logistics solutions.

[0014] Further, based on the current logistics vehicle information and preset constraints, a target logistics solution and a plurality of target logistics vehicles are confirmed from a plurality of logistics solutions, including:

[0015] Determine whether the model of the logistics vehicle in each logistics plan is consistent with the current logistics vehicle information;

[0016] If so, keep the logistics solution as an alternative;

[0017] Determine whether each alternative plan meets the preset constraints;

[0018] If so, keep the alternative as a candidate;

[0019] Obtain the logistics cost of each alternative plan;

[0020] Based on the logistics cost of each candidate solution, a target logistics solution is obtained from several candidate solutions;

[0021] Based on the target logistics plan and current logistics vehicle information, several target logistics vehicles are obtained.

[0022] Furthermore, the preset constraints include:

[0023] The number of shipping addresses for each transport task does not exceed a first preset number;

[0024] and / or the number of delivery addresses for each transport task does not exceed a second preset number;

[0025] And / or there is at least one pickup route between several shipping addresses of each transportation task, and there is at least one delivery route between several receiving addresses.

[0026] Furthermore, the pickup route or delivery route corresponding to the transportation task is obtained, including:

[0027] Obtain several shipping addresses, several receiving addresses and corresponding logistics vehicle models for the transportation task;

[0028] Based on a number of shipping addresses and a number of receiving addresses, a number of pickup routes and a number of delivery routes are obtained;

[0029] Based on the model of the logistics vehicle, obtain the size data of the logistics vehicle;

[0030] Based on the size data of the logistics vehicles, several pick-up routes and several delivery routes to be selected are screened respectively to obtain several pick-up routes and several delivery routes.

[0031] Furthermore, based on the size data of the logistics vehicles, several routes for picking up items and several routes for delivering items are screened respectively, including:

[0032] Obtaining a number of route nodes for each waiting-for-selection pick-up route or each waiting-for-selection delivery route; the route nodes include road conversion nodes, turning nodes, and reversing nodes;

[0033] Based on the size data of the logistics vehicle, obtain the estimated passing status of the logistics vehicle through each route node; the estimated passing status includes passing and failing;

[0034] When the estimated passing status of any route node of a waiting-for-selection connecting route is not passed, the waiting-for-selection connecting route is deleted;

[0035] When the estimated passing status of any route node of a delivery route to be selected is not passing, the delivery route to be selected is deleted.

[0036] Furthermore, the logistics cost of each candidate solution is obtained, including:

[0037] Obtaining a number of transport tasks in the candidate solutions, as well as the logistics vehicle model, a number of pickup routes, and a number of delivery routes corresponding to each transport task;

[0038] Based on the logistics vehicle model, several pick-up routes and several delivery routes corresponding to each transportation task, the logistics cost of each transportation task is obtained;

[0039] Based on the logistics costs of several transportation tasks, the logistics costs of the alternative solutions are confirmed.

[0040] Furthermore, based on the logistics vehicle model, a number of pickup routes, and a number of delivery routes corresponding to each transportation task, the logistics cost of each transportation task is obtained, including:

[0041] Based on a number of pickup routes and a number of delivery routes of the transportation task, a number of transportation routes are obtained;

[0042] Each transportation route includes a pickup route and a delivery route;

[0043] Obtain the pickup and delivery sequence corresponding to each transportation route;

[0044] Based on the pickup sequence and delivery sequence corresponding to each transportation route, a transportation route that meets the preset transportation conditions is obtained as a candidate transportation route;

[0045] Determine the logistics cost of each candidate transportation route based on a number of target transportation routes and logistics vehicle models;

[0046] The candidate transportation route with the lowest logistics cost is obtained as the target transportation route, and the logistics cost of the target transportation route is used as the logistics cost of the corresponding transportation task.

[0047] Furthermore, the preset transportation conditions include:

[0048] The delivery address corresponding to the first shipping address in the pickup order is the same as the last delivery address in the delivery order;

[0049] And / or the shipping address corresponding to the first delivery address in the delivery sequence is the same as the last shipping address in the delivery sequence.

[0050] In a second aspect, the present invention provides an e-commerce logistics management system based on big data, the management system comprising:

[0051] A demand response module, the demand response module is used to obtain logistics vehicle information and multiple e-commerce logistics demands within a preset period, the e-commerce logistics demands include item attributes, shipping address and receiving address; item attributes include item name, volume and weight;

[0052] A scheme confirmation module, the scheme confirmation module is used to confirm a number of logistics schemes based on the attributes of items in multiple e-commerce logistics requirements; each logistics scheme includes a number of logistics vehicles, and the model and transportation task of each logistics vehicle; the transportation task includes a shipping address and a receiving address corresponding to at least one e-commerce logistics requirement;

[0053] A scheme screening module, wherein the scheme screening module is used to confirm a target logistics scheme and a plurality of target logistics vehicles from a plurality of logistics schemes based on current logistics vehicle information and preset constraints;

[0054] A task distribution module is used to associate a number of transportation tasks in a target logistics plan with a number of target logistics vehicles in a one-to-one correspondence, and send them to the corresponding target logistics vehicles.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] In this embodiment, multiple logistics plans are obtained by centrally processing multiple e-commerce logistics demands within a preset period; the transportation capacity of logistics vehicles can be fully utilized; multiple logistics plans are screened by current logistics vehicle information and preset constraints to confirm the target logistics plan and several target logistics vehicles, which can improve the accuracy of the logistics plan; by associating several transportation tasks in the target logistics plan with several target logistics vehicles one by one and sending them to the corresponding target logistics vehicles, the allocation of transportation tasks and the arrangement of logistics vehicles are more accurate and reasonable. The technical problems of low efficiency and easy errors in e-commerce logistics management in the prior art are solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a method step diagram of the e-commerce logistics management method based on big data of the present invention.

[0058] Figure 2 This is a principle block diagram of the e-commerce logistics management system based on big data of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0060] First, as Figure 1 As shown, the present invention provides an e-commerce logistics management method based on big data, and the management method includes:

[0061] S10: Obtaining logistics vehicle information and multiple e-commerce logistics demands within a preset period;

[0062] The e-commerce logistics requirements include item attributes, shipping address, and receiving address; item attributes include item name, volume, and weight;

[0063] In this embodiment, the preset cycles include 6 hours, 12 hours and 24 hours; they can be set according to the development scale and the number of e-commerce logistics needs.

[0064] When e-commerce companies send e-commerce logistics requirements to logistics companies, they need to send the shipping address, receiving address and item attribute information together.

[0065] S20: confirming several logistics solutions based on the attributes of items in multiple e-commerce logistics requirements;

[0066] Each logistics plan includes a number of logistics vehicles, as well as the model and transportation tasks of each logistics vehicle; the transportation task includes at least one shipping address, receiving address and loading quantity corresponding to the e-commerce logistics demand;

[0067] In this embodiment, multiple e-commerce logistics demands within a preset period are met by arranging multiple logistics vehicles to perform corresponding transportation tasks. The transportation task of each logistics vehicle includes at least one shipping address, receiving address, and loading quantity corresponding to an e-commerce logistics demand; in some embodiments, the transportation task of a logistics vehicle includes multiple shipping addresses, receiving addresses, and loading quantities corresponding to multiple e-commerce logistics demands. Logistics vehicles need to pass through multiple shipping addresses for pickup and multiple receiving addresses for delivery;

[0068] In this embodiment, each item required by the e-commerce logistics is transported by at least one logistics vehicle.

[0069] S30: confirming a target logistics plan and a number of target logistics vehicles from a number of logistics plans based on current logistics vehicle information and preset constraints;

[0070] In this embodiment, several logistics solutions are screened through current logistics vehicle information and preset constraints to obtain a target logistics solution and corresponding target logistics vehicles.

[0071] S40: Associating a plurality of transport tasks in the target logistics plan with a plurality of target logistics vehicles one by one, and sending them to the corresponding target logistics vehicles.

[0072] Several transportation tasks in the target logistics plan are sent one by one to the corresponding target logistics vehicles; in this embodiment, the transportation tasks are sent to the smartphone of the driver of the target logistics vehicle; in some embodiments, the transportation tasks can also be sent to the on-board terminal of the target logistics vehicle.

[0073] The specific implementation process of this embodiment is as follows:

[0074] In this embodiment, multiple logistics plans are obtained by centrally processing multiple e-commerce logistics demands within a preset period; the transportation capacity of logistics vehicles can be fully utilized; multiple logistics plans are screened by current logistics vehicle information and preset constraints to confirm the target logistics plan and several target logistics vehicles, which can improve the accuracy of the logistics plan; by associating several transportation tasks in the target logistics plan with several target logistics vehicles one by one and sending them to the corresponding target logistics vehicles, the allocation of transportation tasks and the arrangement of logistics vehicles are more accurate and reasonable. The technical problems of low efficiency and easy errors in e-commerce logistics management in the prior art are solved.

[0075] In this embodiment, based on the attributes of items in multiple e-commerce logistics requirements, several logistics solutions are confirmed, including:

[0076] Obtain logistics solution model;

[0077] The attributes of items in multiple e-commerce logistics demands are input into the logistics solution model to obtain several logistics solutions.

[0078] In this embodiment, the logistics solution model includes a neural network model, and the logistics solution model is obtained by constructing a transportation solution database and training the neural network model; the transportation solution database includes item attributes, logistics solutions, and a mapping relationship between item attributes and logistics solutions.

[0079] In this embodiment, based on the current logistics vehicle information and preset constraints, a target logistics solution and a plurality of target logistics vehicles are confirmed from a plurality of logistics solutions, including:

[0080] Determine whether the model of the logistics vehicle in each logistics plan is consistent with the current logistics vehicle information;

[0081] If so, keep the logistics solution as an alternative;

[0082] Determine whether each alternative plan meets the preset constraints;

[0083] If so, keep the alternative as a candidate;

[0084] Obtain the logistics cost of each alternative plan;

[0085] Based on the logistics cost of each candidate solution, a target logistics solution is obtained from several candidate solutions;

[0086] Based on the target logistics plan and current logistics vehicle information, several target logistics vehicles are obtained.

[0087] The current logistics vehicle information includes all logistics vehicles that can currently perform transportation tasks. When a logistics vehicle model exists in a logistics plan but is not in the current logistics vehicle information, it is determined that the logistics vehicle model in the logistics plan does not match the current logistics vehicle information.

[0088] When the models of all logistics vehicles in a logistics plan exist in the current logistics vehicle information, it is determined whether the models of the logistics vehicles in the logistics plan are consistent with the current logistics vehicle information.

[0089] Multiple alternative plans are screened according to preset constraints to obtain the options to be selected.

[0090] Then, the one with the lowest transportation cost is selected from multiple alternative options as the final option.

[0091] In this embodiment, the preset constraints include:

[0092] The number of shipping addresses for each transport task does not exceed a first preset number;

[0093] and / or the number of delivery addresses for each transport task does not exceed a second preset number;

[0094] And / or there is at least one pickup route between several shipping addresses of each transportation task, and there is at least one delivery route between several receiving addresses.

[0095] In this embodiment, the first preset number includes 3, 4 and 5; the second preset number includes 3, 4 and 5.

[0096] When a transport task has multiple shipping addresses, the logistics vehicle needs to arrive at the multiple shipping addresses in turn to pick up the goods; therefore, there needs to be at least one pickup route between the several shipping addresses; similarly, the logistics vehicle needs to have at least one delivery route between the several receiving addresses.

[0097] In this embodiment, obtaining a pickup route or a delivery route corresponding to a transportation task includes:

[0098] Obtain several shipping addresses, several receiving addresses and corresponding logistics vehicle models for the transportation task;

[0099] Based on a number of shipping addresses and a number of receiving addresses, a number of pickup routes and a number of delivery routes are obtained;

[0100] Based on the model of the logistics vehicle, obtain the size data of the logistics vehicle;

[0101] Based on the size data of the logistics vehicles, several pick-up routes and several delivery routes to be selected are screened respectively to obtain several pick-up routes and several delivery routes.

[0102] In this embodiment, a plurality of pickup routes and a plurality of delivery routes to be selected are screened based on the size data of the logistics vehicles, including:

[0103] Obtaining a number of route nodes for each waiting-for-selection pick-up route or each waiting-for-selection delivery route; the route nodes include road conversion nodes, turning nodes, and reversing nodes;

[0104] Based on the size data of the logistics vehicle, obtain the estimated passing status of the logistics vehicle through each route node; the estimated passing status includes passing and failing;

[0105] When the estimated passing status of any route node of a waiting-for-selection connecting route is not passed, the waiting-for-selection connecting route is deleted;

[0106] When the estimated passing status of any route node of a delivery route to be selected is not passing, the delivery route to be selected is deleted.

[0107] In this embodiment, the logistics cost of each candidate solution is obtained, including:

[0108] Obtaining a number of transport tasks in the candidate solutions, as well as the logistics vehicle model, a number of pickup routes, and a number of delivery routes corresponding to each transport task;

[0109] Based on the logistics vehicle model, several pick-up routes and several delivery routes corresponding to each transportation task, the logistics cost of each transportation task is obtained;

[0110] Based on the logistics costs of several transportation tasks, the logistics costs of the alternative solutions are confirmed.

[0111] In this embodiment, based on the logistics vehicle model, a number of pickup routes, and a number of delivery routes corresponding to each transportation task, the logistics cost of each transportation task is obtained, including:

[0112] Based on a number of pickup routes and a number of delivery routes of the transportation task, a number of transportation routes are obtained;

[0113] Each transportation route includes a pickup route and a delivery route;

[0114] Obtain the pickup and delivery sequence corresponding to each transportation route;

[0115] Based on the pickup sequence and delivery sequence corresponding to each transportation route, a transportation route that meets the preset transportation conditions is obtained as a candidate transportation route;

[0116] Determine the logistics cost of each candidate transportation route based on a number of target transportation routes and logistics vehicle models;

[0117] The candidate transportation route with the lowest logistics cost is obtained as the target transportation route, and the logistics cost of the target transportation route is used as the logistics cost of the corresponding transportation task.

[0118] In this embodiment, the logistics cost of each candidate transportation route is determined according to a number of target transportation routes and logistics vehicle models, including:

[0119] Multiple delivery addresses and multiple delivery addresses are used as transportation nodes of the transportation route to be selected; adjacent transportation nodes constitute transportation sections; and the length of each transportation section is obtained;

[0120] According to the loading quantity of each shipping address and the unloading quantity of each receiving address of the selected transportation route, the total vehicle weight of the logistics vehicle corresponding to each transportation section is obtained;

[0121] Based on the total vehicle weight and length of each transport section, obtain the transportation cost of the logistics vehicle on each transport section;

[0122] Based on the transportation costs of several transportation sections, the transportation cost of the transportation route to be selected is obtained.

[0123] In this embodiment, the preset transportation conditions include:

[0124] The delivery address corresponding to the first shipping address in the pickup order is the same as the last delivery address in the delivery order;

[0125] And / or the shipping address corresponding to the first delivery address in the delivery sequence is the same as the last shipping address in the delivery sequence.

[0126] In this embodiment, the advantage of setting preset transportation conditions for screening is that it can facilitate unloading of logistics vehicles when delivering goods.

[0127] Second, as Figure 2 As shown, the present invention provides an e-commerce logistics management system based on big data, and the management system includes:

[0128] A demand response module, the demand response module is used to obtain logistics vehicle information and multiple e-commerce logistics demands within a preset period, the e-commerce logistics demands include item attributes, shipping address and receiving address; item attributes include item name, volume and weight;

[0129] A scheme confirmation module, the scheme confirmation module is used to confirm a number of logistics schemes based on the attributes of items in multiple e-commerce logistics requirements; each logistics scheme includes a number of logistics vehicles, and the model and transportation task of each logistics vehicle; the transportation task includes a shipping address and a receiving address corresponding to at least one e-commerce logistics requirement;

[0130] A scheme screening module, wherein the scheme screening module is used to confirm a target logistics scheme and a plurality of target logistics vehicles from a plurality of logistics schemes based on current logistics vehicle information and preset constraints;

[0131] A task distribution module is used to associate a number of transportation tasks in a target logistics plan with a number of target logistics vehicles in a one-to-one correspondence, and send them to the corresponding target logistics vehicles.

[0132] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0133] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An e-commerce logistics management method based on big data, characterized by: The management method comprises: Obtaining logistics vehicle information and multiple e-commerce logistics requirements within a preset period, wherein the e-commerce logistics requirements include item attributes, shipping address, and receiving address; item attributes include item name, volume, and weight; Based on the attributes of items in multiple e-commerce logistics requirements, several logistics plans are determined; each logistics plan includes several logistics vehicles, as well as the model and transportation task of each logistics vehicle; the transportation task includes at least one shipping address, receiving address and loading quantity corresponding to the e-commerce logistics requirement; Based on the current logistics vehicle information and preset constraints, confirm the target logistics plan and several target logistics vehicles among several logistics plans; Several transportation tasks in the target logistics plan are associated with several target logistics vehicles one by one, and sent to the corresponding target logistics vehicles.

2. The e-commerce logistics management method based on big data according to claim 1, characterized in that: Based on the attributes of items in multiple e-commerce logistics requirements, several logistics solutions are confirmed, including: Obtain logistics solution model; The attributes of items in multiple e-commerce logistics demands are input into the logistics solution model to obtain several logistics solutions.

3. The e-commerce logistics management method based on big data as claimed in claim 2, characterized in that: Based on the current logistics vehicle information and preset constraints, a target logistics solution and several target logistics vehicles are confirmed from several logistics solutions, including: Determine whether the model of the logistics vehicle in each logistics plan is consistent with the current logistics vehicle information; If so, keep the logistics solution as an alternative; Determine whether each alternative plan meets the preset constraints; If so, keep the alternative as a candidate; Obtain the logistics cost of each alternative plan; Based on the logistics cost of each candidate solution, a target logistics solution is obtained from several candidate solutions; Based on the target logistics plan and current logistics vehicle information, several target logistics vehicles are obtained.

4. The e-commerce logistics management method based on big data as claimed in claim 3, characterized in that: The preset constraints include: The number of shipping addresses for each transport task does not exceed a first preset number; and / or the number of delivery addresses for each transport task does not exceed a second preset number; And / or there is at least one pickup route between several shipping addresses of each transportation task, and there is at least one delivery route between several receiving addresses.

5. The e-commerce logistics management method based on big data as claimed in claim 4, characterized in that: Get the pickup route or delivery route corresponding to the transport task, including: Obtain several shipping addresses, several receiving addresses and corresponding logistics vehicle models for the transportation task; Based on a number of shipping addresses and a number of receiving addresses, a number of pickup routes and a number of delivery routes are obtained; Based on the model of the logistics vehicle, obtain the size data of the logistics vehicle; Based on the size data of the logistics vehicles, several pick-up routes and several delivery routes to be selected are screened respectively to obtain several pick-up routes and several delivery routes.

6. The e-commerce logistics management method based on big data according to claim 5, characterized in that: Based on the size data of the logistics vehicles, several routes for picking up and several routes for delivering are screened, including: Obtaining a number of route nodes for each waiting-for-selection pick-up route or each waiting-for-selection delivery route; the route nodes include road conversion nodes, turning nodes, and reversing nodes; Based on the size data of the logistics vehicle, obtain the estimated passing status of the logistics vehicle through each route node; the estimated passing status includes passing and failing; When the estimated passing status of any route node of a waiting-for-selection connecting route is not passed, the waiting-for-selection connecting route is deleted; When the estimated passing status of any route node of a delivery route to be selected is not passing, the delivery route to be selected is deleted.

7. The e-commerce logistics management method based on big data according to claim 6, characterized in that: Obtain the logistics cost of each alternative, including: Obtaining a number of transport tasks in the candidate solutions, as well as the logistics vehicle model, a number of pickup routes, and a number of delivery routes corresponding to each transport task; Based on the logistics vehicle model, several pick-up routes and several delivery routes corresponding to each transportation task, the logistics cost of each transportation task is obtained; Based on the logistics costs of several transportation tasks, the logistics costs of the alternative solutions are confirmed.

8. The e-commerce logistics management method based on big data according to claim 7, characterized in that: Based on the logistics vehicle model, several pick-up routes and several delivery routes corresponding to each transportation task, the logistics cost of each transportation task is obtained, including: Based on a number of pickup routes and a number of delivery routes of the transportation task, a number of transportation routes are obtained; Each transportation route includes a pickup route and a delivery route; Obtain the pickup and delivery sequence corresponding to each transportation route; Based on the pickup sequence and delivery sequence corresponding to each transportation route, a transportation route that meets the preset transportation conditions is obtained as a candidate transportation route; Determine the logistics cost of each candidate transportation route based on a number of target transportation routes and logistics vehicle models; The candidate transportation route with the lowest logistics cost is obtained as the target transportation route, and the logistics cost of the target transportation route is used as the logistics cost of the corresponding transportation task.

9. The e-commerce logistics management method based on big data according to claim 8, characterized in that: The preset transportation conditions include: The delivery address corresponding to the first shipping address in the pickup order is the same as the last delivery address in the delivery order; And / or the shipping address corresponding to the first delivery address in the delivery sequence is the same as the last shipping address in the delivery sequence.

10. An e-commerce logistics management system based on big data, the system being based on the method according to any one of claims 1 to 9, characterized in that: The system comprises: A demand response module, the demand response module is used to obtain logistics vehicle information and multiple e-commerce logistics demands within a preset period, the e-commerce logistics demands include item attributes, shipping address and receiving address; item attributes include item name, volume and weight; A scheme confirmation module, the scheme confirmation module is used to confirm a number of logistics schemes based on the attributes of items in multiple e-commerce logistics requirements; each logistics scheme includes a number of logistics vehicles, and the model and transportation task of each logistics vehicle; the transportation task includes at least one shipping address and a receiving address corresponding to the e-commerce logistics requirement; A scheme screening module, wherein the scheme screening module is used to confirm a target logistics scheme and a plurality of target logistics vehicles from a plurality of logistics schemes based on current logistics vehicle information and preset constraints; A task distribution module is used to associate a number of transportation tasks in a target logistics plan with a number of target logistics vehicles in a one-to-one correspondence, and send them to the corresponding target logistics vehicles.

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