A vehicle fleet management and scheduling method and system

Abstract

The present invention discloses a fleet management and dispatching method and system, which relates to the field of logistics management; the system includes a vehicle information database, an order generation module, and a dispatching module, and the method includes obtaining the cargo quality, volume information, and cargo starting point and end point information of all to-be-transported orders according to the order generation module; obtaining the vehicle's loading space and loading quality information according to the vehicle information data; using a multi-dimensional weight matching method for matching, and then dispatching the vehicle according to the matching result. The present invention matches the order cargo quantity with the vehicle loading quantity by using a multi-dimensional weight matching method, and uses the degree of convenience, quality matching degree, and volume matching degree for comprehensive evaluation, so that the order cargo quantity and the vehicle loading quantity can be matched to achieve the optimal result of maximum loading, thereby reducing the vehicle's redundant loading space, increasing transportation efficiency, and reducing transportation costs.

Description

Technical Field

[0001] The present invention relates to the field of logistics management, and particularly to a method and system for fleet management and scheduling. Background Art

[0002] With the development of industries such as logistics and transportation, the scale of fleets has been continuously expanding, and the difficulty of management and scheduling has also increased accordingly. In the management of logistics scheduling, how to reliably match the cargo volume of orders with the loading capacity of vehicles, so as to minimize the loading redundancy, increase the transportation efficiency, and reduce the transportation cost is an urgent problem to be solved.

[0003] For example, after retrieval, a patent with the Chinese patent publication number CN111598286A discloses a high-efficiency logistics operation management system, which includes an administrator module, a scheduling management module, and a task carrier module. The scheduling management module includes a dispatcher for module information maintenance and a driver responsible for vehicle services. The scheduling management module includes a fleet management unit and a vehicle management unit. The task carrier module is equipped with a carrier salesman responsible for logistics order creation, management, and dispatching to the scheduling management module. The scheduling management module is provided with a transport capacity query unit, which can comprehensively query the transport capacity and query the historical tasks of any fleet or vehicle.

[0004] The above patent has the following deficiencies: it cannot achieve a reasonable match between the order cargo volume and the vehicle loading capacity. Since in the current logistics freight process, the freight volume of each order is different, there will be many orders with small freight volumes, which will result in more redundant loading space during vehicle transportation, thus increasing the vehicle transportation frequency, reducing the transportation efficiency, and increasing the transportation cost.

[0005] Therefore, the present invention proposes a method and system for fleet management and scheduling. Summary of the Invention

[0006] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose a method and system for fleet management and scheduling.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions:

[0008] A fleet management and scheduling system, which includes:

[0009] A vehicle information database, which is used to collect freight vehicle information, specifically including vehicle models, loading space, loading mass, and vehicle driver information;

[0010] An order generation module, which is used to receive orders and generate order information, specifically including cargo type, cargo origin and destination, sender / receiver information, and cargo mass and volume information;

[0011] A scheduling module, which is used to integrate the order information of the order generation module and the vehicle information in the vehicle information database, and schedule the vehicles.

[0012] A fleet management and scheduling method specifically includes the following steps:

[0013] S1: Obtain the cargo quality, volume information, and cargo starting and ending point information of all pending orders according to the order generation module;

[0014] S2: Obtain the loading space and loading quality information of the vehicles according to the vehicle information data;

[0015] S3: Adopt a multi-dimensional weight matching method for matching, and then perform vehicle scheduling according to the matching results.

[0016] Preferably: In the step S3, in the multi-dimensional weight matching method, the dimensions include the degree of being on the same route, the degree of mass matching, and the degree of volume matching.

[0017] Preferably: In the step S3, the multi-dimensional weight matching method specifically includes the following steps:

[0018] S31: Calculate the matching degree A of the dimension of the degree of being on the same route, the matching degree B of the mass dimension, and the matching degree C of the volume dimension in the multi-dimensions respectively;

[0019] S32: Determine the matching degree weight values of the three dimensions respectively 、 、 , + + = 1;

[0020] S33: Then calculate the total matching degree according to the formula and match the cargo with the highest matching degree with the vehicle;

[0021] S34: Complete the matching of all pending orders according to the steps of S31 to S34.

[0022] Preferably: In the step S31, the calculation method of the matching degree includes the following steps:

[0023] S311: Select one type of vehicle and obtain the total loading mass M and the total loading volume V;

[0024] S312: Obtain the set of all freight orders in the pending order whose cargo quality is less than the total loading mass M and less than the total loading volume V;

[0025] S313: Among all the screened freight order sets, perform various permutations and combinations according to the maximum loading capacity to obtain various combination forms that are less than the total loading mass M and less than the total loading volume V;

[0026] S314: Calculate the total mass within each combination and the total volume , and calculate their ratios with the vehicle's total loading mass M and total loading volume V , , where B is the matching degree in the mass dimension and C is the matching degree in the volume dimension, to obtain the matching degrees in the mass dimension and volume dimension;

[0027] S315: Obtain the starting and ending point information of each type of goods within the combination, plan the transportation path mileage and driving time of each type of goods, and take the average of the mileage and driving time to obtain the average mileage and the average driving time ;

[0028] S316: Determine the average mileage and the average driving time of the overlapping paths;

[0029] S317: Mark the starting points s and ending points o of the n types of goods within the combination on the map, connect the n s as starting points pairwise and the o s as ending points pairwise to form line segments, calculate the sum of the mileage of all line segments and the average mileage , , calculate the sum of the driving times of all line segments and the average driving time , ;

[0030] S318: Calculate the matching degree A of the degree of being on the same route according to the formula , represents the weight coefficient.

[0031] Preferably: In the S1 step, the goods information further includes the goods urgency information J, and the goods urgency information is marked by a percentage, .

[0032] Preferably: In the S318 step, , .

[0033] Preferably: In the S32 step, , , .

[0034] Preferably, the scheduling module further has a function of planning an energy replenishment path, and the path planning method is as follows:

[0035] A1: Collect map information of energy replenishment stations;

[0036] A2: Set an energy remaining replenishment threshold ;

[0037] A3: Obtain the percentage of remaining vehicle energy , when is less than , the system issues an energy replenishment alarm and recommends an energy replenishment station according to the optimal path recommendation logic.

[0038] Preferably, in the step A3, the recommendation logic includes the following steps:

[0039] A31: Obtain the current position and current driving direction of the vehicle;

[0040] A32: Obtain the positions of energy replenishment stations near the vehicle, calculate the distance L from the vehicle position, and calculate the relative position direction of the energy replenishment station to the vehicle;

[0041] A33: Calculate the comprehensive evaluation of the final path for each energy replenishment station according to the formula , and then select the energy replenishment station with the smallest result as the optimal replenishment station for recommendation.

[0042] The beneficial effects of the present invention are as follows:

[0043] By adopting a multi-dimensional weight matching method to match the order quantity with the vehicle loading capacity, and using the degree of being on the same route, the degree of quality matching, and the degree of volume matching for comprehensive evaluation, the present invention can achieve the optimal result matching of the maximum loading of the order quantity and the vehicle loading capacity, thereby reducing the redundant loading space of the vehicle, increasing the transportation efficiency, and reducing the transportation cost.

[0044] In the evaluation of the degree of being on the same route, the present invention uses a comprehensive evaluation of distance and time with the help of a navigation software, and on this basis, adopts a comprehensive calculation method of path superposition, multi-dimensional mean value of the starting point, and multi-dimensional mean value of the ending point for the degree of being on the same route, which can make the final result of the degree of being on the same route more reasonable, thereby increasing the optimality of the subsequent matching.

[0045] By setting the function of planning an energy replenishment path, the present invention can timely remind of energy replenishment, increase the transportation reliability. In addition, when planning the path, a comprehensive calculation of the cosine value of the included angle between the distance and the direction is adopted, so that the path planning can not only ensure a shorter path but also ensure the direction fit with the destination, thereby increasing the path planning accuracy and also increasing the transportation efficiency. Description of the Drawings

[0046] Figure 1 This is an architecture diagram of a vehicle fleet management and scheduling system proposed by the present invention;

[0047] Figure 2 This is a scheduling logic diagram of a vehicle fleet management and scheduling method proposed by the present invention;

[0048] Figure 3 This is a matching logic diagram of a vehicle fleet management and scheduling method proposed by the present invention. Specific embodiments

[0049] The technical solution of the present invention will be further described in detail below in conjunction with specific embodiments.

[0050] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "installation", "connection", "connection", and "setting" should be understood in a broad sense. For example, it can be fixedly connected and set, or detachably connected and set, or integrally connected and set. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations. Embodiment 1:

[0051] A vehicle fleet management and scheduling system, which includes:

[0052] A vehicle information database, which is used to collect freight vehicle information, specifically including vehicle models, loading spaces, loading masses, and vehicle driver information;

[0053] An order generation module, which is used to receive orders and generate order information, specifically including cargo types, cargo starting and ending points, sender / receiver information, and cargo mass and volume information;

[0054] A scheduling module, which is used to integrate the order information of the order generation module and the vehicle information of the vehicle information database to schedule the vehicles. Embodiment 2:

[0055] A vehicle fleet management and scheduling method, which is the scheduling logic of the scheduling module, specifically including the following steps:

[0056] S1: Obtain the cargo mass, volume information, and cargo starting and ending point information of all pending orders according to the order generation module;

[0057] S2: Obtain the loading space and loading mass information of the vehicles according to the vehicle information data;

[0058] S3: Use a multi-dimensional weight matching method for matching, and then perform vehicle scheduling according to the matching results.

[0059] In the step S3, in the multi-dimensional weight matching method, the dimensions include the degree of being on the same route, the degree of quality matching, and the degree of volume matching.

[0060] In the step S3, the multi-dimensional weight matching method specifically includes the following steps:

[0061] S31: Calculate the matching degree A of the dimension of the degree of being on the same route, the matching degree B of the quality dimension, and the matching degree C of the volume dimension in the multi-dimensions respectively;

[0062] S32: Determine the matching degree weight values of the three dimensions respectively 、 、 , + + = 1;

[0063] S33: Then calculate the total matching degree according to the formula and then match the goods and the vehicle with the highest matching degree;

[0064] S34: Complete the matching of all orders to be transported according to the steps from S31 to S34.

[0065] In the step S31, the calculation method of the matching degree includes the following steps:

[0066] S311: Select one type of vehicle and obtain the total loading mass M and the total loading volume V;

[0067] S312: Obtain the set of all freight orders in the order to be transported where the mass of the goods is less than the total loading mass M and less than the total loading volume V;

[0068] S313: In all the screened freight order sets, perform various permutations and combinations according to the maximum loading capacity to obtain various combination forms that are less than the total loading mass M and less than the total loading volume V. For example, if the screened freight orders are 4, which are goods a (mass 1, volume 1), goods b (mass 2, volume 3), goods c (mass 3, volume 5), goods d (mass 4, volume 7), and the total loading mass of the vehicle is 6 and the total loading volume is 10, then the combinations obtained after arranging according to the maximum loading capacity are abc, ad, bd. Although the combinations ab and ac can also be loaded by the vehicle, their redundant loading space is still relatively large, so they are discarded;

[0069] S314: Calculate the total mass and the total volume within each combination, and calculate the ratios with the total loading mass M and the total loading volume V of the vehicle , , where B is the matching degree of the quality dimension and C is the matching degree of the volume dimension, obtaining the matching degree of the quality dimension and the matching degree of the volume dimension;

[0070] S315: Obtain the starting and ending information of each kind of goods in the combination, plan the transportation path mileage and driving time of each kind of goods (this step can be implemented with the help of a navigation software), and take the average value of the mileage and driving time to obtain the average mileage and the average driving time ;

[0071] S316: Determine the average mileage and the average driving time ;

[0072] S317: Mark the starting points s and ending points o of n kinds of goods in the combination on the map, connect the n s as starting points in pairs, and connect the o s as ending points in pairs to form line segments, calculate the sum of the mileage of all line segments and the average mileage , , calculate the sum of the driving time of all line segments and the average driving time , ;

[0073] S318: Calculate the matching degree A of the convenience degree according to the formula , represents the weight coefficient.

[0074] In the S1 step, the goods information further includes the goods urgency information J, and the goods urgency information is marked by a percentage. .

[0075] In the S318 step, , .

[0076] In the S32 step, , , .

[0077] Embodiment 3:

[0078] A fleet management and dispatching method, which is the dispatching logic of the dispatching module, specifically includes the following steps:

[0079] S1: Obtain the goods quality, volume information and the goods starting and ending information of all pending orders according to the order generation module;

[0080] S2: Obtain the loading space and loading quality information of the vehicle according to the vehicle information data;

[0081] S3: Adopt a weight matching method based on multiple dimensions for matching, and then perform vehicle scheduling according to the matching results.

[0082] In the step S3, in the weight matching method based on multiple dimensions, the dimensions include the degree of being on the same route, the degree of quality matching, and the degree of volume matching.

[0083] The weight matching method based on multiple dimensions in the step S3 specifically includes the following steps:

[0084] S31: Calculate the matching degree A of the degree of being on the same route dimension, the matching degree B of the quality dimension, and the matching degree C of the volume dimension in multiple dimensions respectively;

[0085] S32: Determine the matching degree weight values of the three dimensions respectively , , , + + = 1;

[0086] S33: Then calculate the total matching degree according to the formula and match the goods and vehicles with the highest matching degree;

[0087] S34: Complete the matching of all orders to be transported according to the steps from S31 to S34.

[0088] In the step S31, the calculation method of the matching degree includes the following steps:

[0089] S311: Select one type of vehicle and obtain the total loading mass M and the total loading volume V;

[0090] S312: Obtain all freight order sets in which the mass of the goods in the order to be transported is less than the total loading mass M and less than the total loading volume V;

[0091] S313: In all screened freight order sets, perform various permutations and combinations according to the maximum loading capacity to obtain various combination forms less than the total loading mass M and less than the total loading volume V. For example, if the screened freight orders are 4, which are goods a (mass 1, volume 1), goods b (mass 2, volume 3), goods c (mass 3, volume 5), goods d (mass 4, volume 7), and the total loading mass of the vehicle is 6 and the total loading volume is 10, then the combinations obtained after arranging according to the maximum loading capacity are abc, ad, bd. Although the combinations ab and ac can also be loaded by the vehicle, their redundant loading space is still relatively large, so they are discarded;

[0092] S314: Calculate the total mass within each combination and the total volume , and calculate the ratios of it to the total loaded mass M and the total loaded volume V of the vehicle , , where B is the matching degree in terms of mass dimension and C is the matching degree in terms of volume dimension, to obtain the matching degrees in mass dimension and volume dimension;

[0093] S315: Obtain the starting and ending information of each kind of goods in the combination, plan the transportation path mileage and driving time of each kind of goods (this step can be implemented with the help of a navigation software), and take the average of the mileage and driving time to respectively obtain the average mileage and the average driving time ;

[0094] S316: Determine the average mileage and the average driving time of the overlapping paths;

[0095] S317: Mark the starting points s and ending points o of the n kinds of goods in the combination on the map, connect the n s as starting points pairwise and connect the o s as ending points pairwise to form line segments, calculate the sum of the mileage of all line segments and the average mileage , , calculate the sum of the driving time of all line segments and the average driving time , ;

[0096] S318: Calculate the matching degree A of the degree of being on the same route according to the formula , represents the weight coefficient.

[0097] In the S1 step, the goods information further includes the goods urgency information J, and the goods urgency information is marked by a percentage .

[0098] In the S318 step , .

[0099] In the S32 step , , .

[0100] Example 4:

[0101] A fleet management and scheduling method, which is the scheduling logic of a scheduling module, specifically includes the following steps:

[0102] S1: Obtain the cargo quality, volume information, and cargo starting and ending point information of all orders to be shipped according to the order generation module;

[0103] S2: Obtaining the loading space and loading mass information of the vehicle according to the vehicle information data;

[0104] S3: Use a multi-dimensional weight matching method for matching, and then dispatch vehicles based on the matching results.

[0105] In the step S3, in the multi-dimensional weight matching method, the dimensions include the degree of being on the way, the degree of quality matching and the degree of volume matching.

[0106] In the step S3, the multi-dimensional weight matching method specifically includes the following steps:

[0107] S31: respectively calculating the matching degree A of the on-the-way degree dimension, the matching degree B of the quality dimension, and the matching degree C of the volume dimension in the multi-dimensionality;

[0108] S32: Determine the matching weight values ​​of the three dimensions respectively , , , + + =1;

[0109] S33: Then according to the formula Calculate the total matching degree, and then match the goods and vehicles with the highest matching degree;

[0110] S34: According to the steps from S31 to S34, all the orders to be shipped are matched.

[0111] In the step S31, the method for calculating the matching degree includes the following steps:

[0112] S311: Select one type of vehicle and obtain the total loaded mass M and the total loaded volume V;

[0113] S312: Obtain a set of all freight orders in the to-be-shipped orders whose cargo weight is less than the total loading weight M and less than the total loading volume V;

[0114] S313: Among all the screened freight order sets, perform various permutations and combinations according to the maximum loading capacity to obtain various combination forms that are less than the total loading mass M and less than the total loading volume V. For example, if there are 4 screened freight orders, namely cargo a (mass 1, volume 1), cargo b (mass 2, volume 3), cargo c (mass 3, volume 5), and cargo d (mass 4, volume 7), the total loading mass of the vehicle is 6, and the total loading volume is 10, then the combinations obtained after arranging according to the maximum loading capacity are abc, ad, and bd. Although the combinations ab and ac can also be loaded by the vehicle, their redundant loading space is still relatively large, so they are discarded;

[0115] S314: Calculate the total mass and total volume within each combination, and take the ratios of them to the total loading mass M and total loading volume V of the vehicle , , where B is the matching degree in the mass dimension and C is the matching degree in the volume dimension, to obtain the matching degrees in the mass dimension and volume dimension;

[0116] S315: Obtain the starting and ending point information of each type of cargo within the combination, plan the transportation path mileage and driving time of each type of cargo (this step can be achieved with the help of a navigation software), and take the average of the mileage and driving time to obtain the average mileage and average driving time ;

[0117] S316: Determine the average mileage and average driving time of the overlapping paths;

[0118] S317: Mark the starting points s and ending points o of the n types of cargo within the combination on the map, connect the n s as starting points in pairs, and connect the o as ending points in pairs to form line segments, calculate the sum of the mileage of all line segments and the average mileage , , calculate the sum of the driving times of all line segments and the average driving time , ;

[0119] S318: Calculate the matching degree A of the degree of being on the same route according to the formula , represents the weight coefficient.

[0120] In the said S1 step, the cargo information further includes the cargo urgency information J, and the cargo urgency information is marked in percentage .

[0121] In the step S318, , .

[0122] In the step S32, , , .

[0123] Embodiment 5:

[0124] A vehicle fleet management and scheduling method, which is the scheduling logic of a scheduling module, specifically includes the following steps:

[0125] S1: Obtain the cargo quality, volume information, and cargo origin and destination information of all orders to be transported according to the order generation module;

[0126] S2: Obtain the loading space and loading quality information of the vehicle according to the vehicle information data;

[0127] S3: Adopt a multi-dimensional weight matching method for matching, and then perform vehicle scheduling according to the matching result.

[0128] In the step S3, in the multi-dimensional weight matching method, its dimensions include the degree of being on the same route, the degree of quality matching, and the degree of volume matching.

[0129] In the step S3, the multi-dimensional weight matching method specifically includes the following steps:

[0130] S31: Calculate the matching degree A of the on-the-same-route dimension, the matching degree B of the quality dimension, and the matching degree C of the volume dimension in the multi-dimensions respectively;

[0131] S32: Determine the matching degree weight values of the three dimensions respectively , , , + + = 1;

[0132] S33: Then calculate the total matching degree according to the formula , and then match the cargo with the highest matching degree with the vehicle;

[0133] S34: According to the steps of S31 to S34, match all orders to be transported.

[0134] In the step S31, the calculation method of the matching degree includes the following steps:

[0135] S311: Select one type of vehicle and obtain the total loading mass M and the total loading volume V;

[0136] S312: Obtain all freight order sets in the to-be-transported orders where the quality of the goods is less than the total loading mass M and less than the total loading volume V;

[0137] S313: In all the screened freight order sets, perform various permutations and combinations according to the maximum loading capacity to obtain various combination forms that are less than the total loading mass M and less than the total loading volume V. For example, if the screened freight orders are 4, namely goods a (quality 1, volume 1), goods b (quality 2, volume 3), goods c (quality 3, volume 5), and goods d (quality 4, volume 7), and the total loading mass of the vehicle is 6 and the total loading volume is 10, then the combinations obtained after arranging according to the maximum loading capacity are abc, ad, and bd. Although the combinations ab and ac can also be loaded by the vehicle, their redundant loading space is still relatively large, so they are discarded;

[0138] S314: Calculate the total mass and the total volume within each combination, and take the ratios with the total loading mass M and the total loading volume V of the vehicle . , where B is the matching degree in the mass dimension and C is the matching degree in the volume dimension, to obtain the matching degree in the mass dimension and the matching degree in the volume dimension;

[0139] S315: Obtain the starting point and ending point information of each kind of goods within the combination, plan the transportation path mileage and driving time of each kind of goods (this step can be realized with the help of a navigation software), and take the average value of the mileage and the driving time to obtain the average mileage and the average driving time respectively;

[0140] S316: Determine the average mileage and the average driving time of the overlapping paths;

[0141] S317: Mark the starting points s and ending points o of the n kinds of goods within the combination on the map, connect the n s as starting points in pairs and connect the o as ending points in pairs to form line segments, calculate the sum of the mileage of all line segments and the average mileage , , calculate the sum of the driving time of all line segments and the average driving time , ;

[0142] S318: Calculate the matching degree A of the degree of being on the same route according to the formula , represents the weight coefficient.

[0143] In the S1 step, the goods information further includes the goods urgency information J, and the goods urgency information is marked by a percentage. .

[0144] In the S318 step, , .

[0145] In the S32 step, , , .

[0146] The scheduling module also has a function of planning the energy replenishment path, and the path planning method is as follows:

[0147] A1: Collect the map information of the energy replenishment stations. For fuel vehicles, the energy replenishment stations are gas stations; for electric vehicles, they are charging stations; for hybrid vehicles, they are gas stations and charging stations.

[0148] A2: Set the remaining energy replenishment threshold , which represents that when the remaining vehicle energy is lower than , energy replenishment is required.

[0149] A3: Obtain the remaining vehicle energy percentage . When is less than , the system issues an energy replenishment alarm and recommends an energy replenishment station according to the optimal path recommendation logic.

[0150] In the A3 step, the recommendation logic includes the following steps:

[0151] A31: Obtain the current position and current driving direction of the vehicle.

[0152] A32: Obtain the positions of the energy replenishment stations near the vehicle, calculate the distance L from the vehicle position, and calculate the relative position direction of the energy replenishment station to the vehicle.

[0153] A33: Calculate the comprehensive evaluation of the final path for each energy replenishment station according to the formula , and then select the energy replenishment station with the smallest result as the optimal replenishment station for recommendation.

[0154] As mentioned above, the above is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A fleet management and dispatching method, characterized in that: The specific steps include: S1: Obtain the cargo quality, volume information, and cargo starting and ending point information of all orders to be shipped according to the order generation module; S2: Obtaining the loading space and loading mass information of the vehicle according to the vehicle information data; S3: The dispatch module uses a multi-dimensional weight matching method to perform matching, and then dispatches vehicles based on the matching results; In the step S3, in the multi-dimensional weight matching method, the dimensions include the degree of being on the way, the degree of quality matching and the degree of volume matching; In the step S3, the multi-dimensional weight matching method specifically includes the following steps: S31: respectively calculating the matching degree A of the on-the-way degree dimension, the matching degree B of the quality dimension, and the matching degree C of the volume dimension in the multi-dimensionality; S32: Determine the matching weight values ​​of the three dimensions respectively , , , + + =1; S33: Then according to the formula Calculate the total matching degree, and then match the goods and vehicles with the highest matching degree; S34: According to the steps from S31 to S34, all the orders to be shipped are matched; In the step S31, the method for calculating the matching degree includes the following steps: S311: Select one type of vehicle and obtain the total loaded mass M and the total loaded volume V; S312: Obtain a set of all freight orders in the to-be-shipped orders whose cargo weight is less than the total loading weight M and less than the total loading volume V; S313: In all the filtered freight order sets, multiple permutations and combinations are performed according to the maximum loading volume to obtain multiple combinations that are less than the total loading mass M and less than the total loading volume V; S314: Calculate the total mass of each combination and total volume and compare it with the vehicle's total loading mass M and total loading volume V , , where B is the matching degree of the quality dimension, and C is the matching degree of the volume dimension, and the quality dimension matching degree and the volume dimension matching degree are obtained; S315: Obtain the starting point and end point information of each cargo in the combination, plan the transportation route mileage and travel time of each cargo, and take the average of the mileage and travel time to obtain the average mileage and average travel time ; S316: Determine the average mileage of overlapping paths and average travel time ; S317: For the n types of goods in the combination, the starting point s and the end point o are marked on the map, and the n s as the starting point are connected in pairs, and the o as the end point are connected in pairs to form a line segments, calculate the mileage and and average mileage , , calculate the travel time and and average travel time , ; S318: According to the formula Calculate the matching degree A of the degree of on-the-way, represents the weight coefficient; In the step S1, the cargo information also includes cargo urgency information J, which is marked in percentage. ; In the step S318, , ; In the step S32, , , .

2. A fleet management and dispatching method according to claim 1, characterized in that: The scheduling module also has an energy supply path planning function, and the path planning method is: A1: Contains map information of energy supply stations; A2: Set the energy remaining supply threshold ; A3: Get the remaining energy percentage of the vehicle ,when Less than When the energy replenishment alarm is triggered, the system will issue an energy replenishment alarm and recommend energy supply stations according to the optimal path recommendation logic.

3. A fleet management and dispatching method according to claim 2, characterized in that: In step A3, the recommendation logic includes the following steps: A31: Get the current position and driving direction of the vehicle; A32: Obtain the location of the energy supply station near the vehicle, calculate the distance L from the vehicle, and calculate the direction of the energy supply station relative to the vehicle; A33: According to the formula Calculate the final path comprehensive evaluation of each energy supply station, and then select the energy supply station with the smallest result as the optimal supply station for recommendation.

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