Freight vehicle matching method and matching device

Abstract

The application discloses a freight vehicle matching method and a matching device, and solves the technical problems of the existing vehicle matching scheme, such as scattered transport capacity pool, complex matching scheme implementation, and low vehicle utilization rate. The freight vehicle matching method comprises the following steps: receiving order data; calculating the idle rate of each vehicle type in each vehicle team in the transport capacity pool at a time point when the order arrives; calculating the vehicle type priority of each vehicle type in each vehicle team according to the idle rate; calculating the vehicle team priority of each vehicle team according to the vehicle type priority of all vehicle types possessed by the vehicle team; establishing a vehicle configuration model according to the vehicle team priority and the decision variable of the vehicle team; solving the vehicle configuration model to obtain the value of the decision variable of each vehicle team, and determining a matched vehicle team according to the value of the decision variable; and determining a matched vehicle according to the vehicle type and the idle rate of the vehicle in the matched vehicle team.

Description

Technical Field

[0001] This invention belongs to the field of intelligent logistics technology, specifically, it relates to a method and device for matching freight vehicles. Background Technology

[0002] In the freight industry, intelligent freight platform systems act as a bridge connecting shippers and vehicle owners, providing transaction services where shippers post orders on the platform and vehicle owners receive orders through the platform. Currently, freight platform systems have a large number of individual vehicle owners, but they are scattered across the market. Matching freight vehicles to maximize the interests of both shippers and vehicle owners is one of the key tasks of freight platform systems.

[0003] For example, Chinese patent application CN109215333A discloses a scheduling configuration method and system. The cloud server receives task data sent by the user, including task load and task time, and also receives vehicle status data sent by the vehicle terminal, including vehicle model information, vehicle load and vehicle idle time. Based on the task data and vehicle status data, a task vehicle scheme is determined. The task vehicle scheme includes vehicle model information and the corresponding quantity of vehicle models. The cloud server arranges and combines vehicle models and vehicle quantities to obtain multiple vehicle models that can perform tasks and the required number of vehicles, thus determining multiple task vehicle schemes.

[0004] The technical solutions disclosed in the aforementioned patent applications treat each vehicle as an independent entity, obtaining a task vehicle scheme by arranging and combining the vehicle status data of each vehicle. While this can allocate the required vehicles to users, the fragmented nature of the fleet due to each vehicle being an independent entity leads to a lack of effective vehicle management, making it difficult to guarantee service and pricing. Therefore, users do not want to be matched with the required vehicles from scattered individual vehicles, especially when there are multiple usage needs; they would prefer to be matched with a fleet of a certain size. This also reduces the probability of matching scattered individual vehicles with usage needs, affecting the order acceptance rate and cost-effectiveness of individual vehicles. Moreover, arranging and combining each vehicle to determine the matching task vehicle is complex and makes it difficult to achieve optimal vehicle utilization, resulting in high idle rates for some vehicles.

[0005] Although existing technologies allow for order taking on freight platform systems in the form of fleets, whether or not a vehicle belongs to a fleet is only a preferred criterion. When matching vehicles, individual vehicles are still used as the matching unit. Therefore, there are still technical problems such as the complexity of the solution implementation and the difficulty in making full use of vehicles. Summary of the Invention

[0006] One of the objectives of this invention is to provide a freight vehicle matching method that solves the technical problems of existing vehicle matching schemes, such as scattered transport capacity pools, complex matching scheme implementation, and low vehicle utilization.

[0007] To achieve the above-mentioned objectives, the freight vehicle matching method provided by this invention adopts the following technical solution:

[0008] A method for matching freight vehicles, wherein the freight vehicle capacity pool comprises multiple fleets, and each fleet comprises several vehicles; the freight vehicle matching method includes:

[0009] Receive data for order i; the data for order i includes the quantity Q of the required vehicle model k. ik ;

[0010] Calculate the idle rate λ of each vehicle type k in each fleet j of the capacity pool at the time when order i arrives. jk :

[0011] According to the idle rate λ jk Calculate the vehicle priority for each vehicle type k in each fleet j. Vehicle type priority With the idle rate λ jk A positive correlation is satisfied;

[0012] Based on the vehicle priority of all vehicle types k possessed by each fleet j. Calculate the fleet priority of fleet j.

[0013] Based on the decision variable x of team j ij The aforementioned fleet priority The M jk and the Q mentioned above ik Establish a vehicle configuration model;

[0014] Solve the vehicle configuration model to obtain the decision variable x for each fleet j. ij The value of the decision variable is used to determine the matching fleet;

[0015] The matching vehicles are determined based on the vehicle type and availability rate of the vehicles in the matched fleet.

[0016] Where i is the order number; j is the fleet number, j = 1, 2, ..., n, where n is the total number of fleets in the capacity pool; k is the vehicle model number, k = 1, 2, ..., m, where m is the total number of vehicle models in the capacity pool; M jk N represents the number of idle vehicles of model k in fleet j; jk x is the total number of all vehicles of type k in fleet j; ij Let x be the decision variable for vehicle j, taking values ​​of 0 or 1. ij =1 indicates that order i and fleet j are successfully matched, xij =0 indicates that order i and fleet j were not successfully matched.

[0017] In other embodiments of this application, the vehicle configuration model includes the following objective function and constraints:

[0018]

[0019]

[0020] In other embodiments of this application, the vehicle configuration model includes the following objective function and constraints:

[0021]

[0022]

[0023] Where ρ is a known weight value.

[0024] In other embodiments of this application, based on the idle rate λ jk Calculate the vehicle priority for each vehicle type k in each fleet j. Specifically, it includes:

[0025] The priority of each vehicle type k is calculated using the following method.

[0026] In other embodiments of this application, the priority is based on the aforementioned priority of all vehicle types k possessed by each fleet j. Calculate the fleet priority of fleet j. Specifically, it includes:

[0027] The fleet priority is calculated in the following manner.

[0028] In other embodiments of this application, the freight vehicle matching method further includes:

[0029] When a freight vehicle joins the capacity pool, it can choose to open a new fleet or join an existing fleet in the capacity pool.

[0030] To achieve the aforementioned objectives, the freight vehicle matching device provided by this invention employs the following technical solution:

[0031] A freight vehicle matching device, wherein the freight vehicles belong to a capacity pool comprising multiple fleets, each fleet comprising a number of vehicles; the freight vehicle matching device includes:

[0032] The order data receiving module is used to receive data for order i; the data for order i includes the quantity Q of the required vehicle model k. ik ;

[0033] The idle rate calculation module is used to calculate the idle rate λ of each vehicle type k in each fleet j in the capacity pool at the time when order i arrives. jk :

[0034] The vehicle type priority calculation module is used to calculate the vehicle type priority based on the idle rate λ. jk Calculate the vehicle priority for each vehicle type k in each fleet j. Vehicle type priority With the idle rate λ jk A positive correlation is satisfied;

[0035] The fleet priority calculation module is used to calculate the vehicle priority based on the vehicle type priority of all vehicle types k owned by each fleet j. Calculate the fleet priority of fleet j.

[0036] The vehicle configuration model building module is used to establish the decision variable x of fleet j. ij The aforementioned fleet priority The M jk and the Q mentioned above ik Establish a vehicle configuration model;

[0037] The model solving and vehicle matching module is used to solve the vehicle configuration model and obtain the decision variable x for each fleet j. ij The value of the decision variable is used to determine the matching fleet, and the matching vehicle is determined based on the vehicle type and idle rate of the vehicles in the matching fleet.

[0038] Where i is the order number; j is the fleet number, j = 1, 2, ..., n, where n is the total number of fleets in the capacity pool; k is the vehicle model number, k = 1, 2, ..., m, where m is the total number of vehicle models in the capacity pool; M jk N represents the number of idle vehicles of model k in fleet j; jk x is the total number of all vehicles of type k in fleet j; ij Let x be the decision variable for vehicle j, taking values ​​of 0 or 1. ij =1 indicates that order i and fleet j are successfully matched, x ij =0 indicates that order i and fleet j were not successfully matched.

[0039] In other embodiments of this application, the freight vehicle matching device further includes:

[0040] The fleet selection module is used to allow freight vehicles to choose to open a new fleet or join an existing fleet in the capacity pool when joining the capacity pool.

[0041] Another object of the present invention is to provide an electronic device including a processor, a memory and a computer program stored in the memory, wherein the processor is configured to execute the computer program to implement the above-described freight vehicle matching method.

[0042] Another object of the present invention is to provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described freight vehicle matching method.

[0043] Compared with the prior art, the advantages and positive effects of the present invention are:

[0044] The freight vehicle matching method and device provided by this invention involve assigning each vehicle in a capacity pool to a fleet, forming a capacity pool with multiple fleets. During vehicle matching, orders are broken down into the required vehicle type and the corresponding number of vehicles for each type. At the order arrival time, fleet priority is determined based on the idle rate of vehicles in the fleet. A vehicle configuration model is then constructed based on the fleet priority and the fleet's decision variables. Solving the model achieves the matching of fleets and vehicles within them. By grouping vehicles into multiple fleets and then using the fleet as the processing unit to construct the vehicle configuration model for vehicle matching, unified fleet management enables the integration of vehicle capacity resources and the management of each vehicle, improving management efficiency and vehicle-cargo matching efficiency. Determining fleet priority based on vehicle idle rate and constructing a configuration model based on fleet priority for vehicle matching reduces vehicle idle rate and improves vehicle utilization. Compared to existing simple permutation and combination methods, vehicle matching using a vehicle configuration model is simpler and more effective.

[0045] Other features and advantages of the present invention will become clearer after reading the detailed embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart of an embodiment of the freight vehicle matching method proposed in this invention;

[0048] Figure 2 This is a schematic diagram of the structure of an embodiment of the freight vehicle matching device proposed in this invention;

[0049] Figure 3 This is a schematic diagram of the structure of an embodiment of the electronic device proposed in this invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] It should be noted that the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they can be implemented by those skilled in the art. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0052] Figure 1 This is a flowchart illustrating one embodiment of the freight vehicle matching method proposed in this invention. In this embodiment, the freight vehicle capacity pool comprises multiple fleets, each fleet consisting of several vehicles, with each vehicle belonging to one of the fleets. That is, vehicles join fleets, and numerous fleets converge to form the capacity pool of the freight platform system. The platform system manages the fleets uniformly, efficiently completing vehicle matching and dispatch.

[0053] like Figure 1 As shown, this embodiment uses the following process for matching freight vehicles.

[0054] S11: Receive order data.

[0055] Let order number i be. Break down order i into different types of vehicle requirements, and determine the data for order i. The data for order i includes the vehicle type k required to complete order i and the quantity Q of that vehicle type needed. ik Where k is the vehicle model number, k = 1, 2, ..., m, and m is the total number of vehicle models in the capacity pool. After order i is determined, based on its freight volume, the known vehicle model information in the capacity pool, etc., it can be easily split to obtain the required vehicle model k and the required quantity Q of that vehicle model. ik .

[0056] S12: Calculate the idle rate of each vehicle type in each fleet in the capacity pool at the time when the order arrives.

[0057] This embodiment matches vehicles based on a specific point in time. At the time an order arrives, the available vehicles in the capacity pool are static and deterministic.

[0058] Define the fleet numbers in the capacity pool as j, j = 1, 2, ..., n, where n is the total number of fleets in the capacity pool, and define M. jk N represents the number of idle vehicles of model k in fleet j. jk Let be the total number of all vehicles of type k in fleet j. Then, at the time when order i arrives, what is the idle rate λ of each type k in each fleet j of the capacity pool? jk The calculation formula is:

[0059] S13: Calculate the vehicle priority for each vehicle type in each fleet based on the idle rate.

[0060] Vehicle type priority is defined as This represents the vehicle priority for each vehicle type k in each fleet j. Vehicle priority The idle rate λ of the vehicle type determined according to S12 jk Confirmed, and vehicle model priority. With idle rate λ jk A positive correlation is maintained. That is, the higher the idle rate of a vehicle model, the higher its priority. All factors that increase vehicle priority... With idle rate λ jk All implementations that satisfy a positive correlation are within the protection scope of this invention.

[0061] S14: Calculate the team priority based on the vehicle priority of all vehicles owned by each team.

[0062] The priority of team j is used express.

[0063] The purpose of setting fleet priority is to prioritize matching fleets with high idle rates when building vehicle configuration models, thereby achieving a balance in fleet cargo receiving.

[0064] In some embodiments, fleet priority can be calculated using vehicle type priority in various ways. For example, the fleet priority can be obtained by directly summing the priorities of all vehicle types, or by using the average of the priorities of all vehicle types as the fleet priority.

[0065] In some other embodiments, the following weighted average is used to determine fleet priority:

[0066]

[0067] By using a weighted average to determine fleet priority, the configuration of different vehicle types within the fleet can be taken into account, making the calculated priorities of different fleets more consistent and comparable, thus improving modeling accuracy and vehicle matching effectiveness.

[0068] S15: Establish a vehicle configuration model based on the fleet's decision variables and fleet priorities.

[0069] Specifically, it is based on the decision variable x of team j. ij fleet priority The number of idle vehicles M of model k in fleet j jk And the quantity Q of a certain car model required for order i. ik Establish a vehicle configuration model.

[0070] x ij As a decision variable for vehicle fleet j, its value can be either 0 or 1. ij =1, indicating that order i and fleet j are successfully matched, x ij =0 indicates that order i and fleet j were not successfully matched.

[0071] When establishing the vehicle configuration model, priority is given to matching fleets with high priority, and the dispersion of matched fleets is minimized. Therefore, when there is a fleet with an independent order i, its priority will be higher than a combination of a group of smaller fleets with lower idle rates.

[0072] S16: Solve the vehicle configuration model to obtain the values ​​of the decision variables for each fleet, and determine the matching fleet and matching vehicles based on the values ​​of the decision variables.

[0073] Whether a fleet can be matched is determined by whether its decision variable is 0 or 1. That is, fleets with a decision variable value of 1 will be matched. Among the matched fleets, the final matched vehicles are determined based on the vehicle type and availability rate of vehicles that match order i.

[0074] Using the aforementioned freight vehicle matching method, each vehicle in the capacity pool is assigned to a fleet, forming a capacity pool with multiple fleets. During vehicle matching, orders are broken down into the required vehicle type and the corresponding number of vehicles. At the order arrival time, fleet priority is determined based on the idle rate of vehicles in the fleet. Then, a vehicle configuration model is constructed based on the fleet priority and the fleet's decision variables. Solving the model achieves the matching of fleets and vehicles within them. By grouping vehicles into multiple fleets and then using the fleet as the processing unit to construct a vehicle configuration model for vehicle matching, unified fleet management enables the integration of vehicle capacity resources and the management of each vehicle, improving management efficiency and freight matching efficiency. Determining fleet priority based on vehicle idle rate and constructing a configuration model based on fleet priority for vehicle matching reduces vehicle idle rate and improves vehicle utilization. Compared to existing simple permutation and combination methods, vehicle matching using a vehicle configuration model is simpler and more effective.

[0075] In some embodiments, a first vehicle matching model is established, including an objective function and constraints, as follows:

[0076]

[0077]

[0078] Where st is a constraint, representing the number of idle vehicles of vehicle type k in all fleets j for any vehicle type k. jk The decision variable x of the team j ij The sum of the products is not less than the quantity of that model Q required for order i. ik And in the objective function, This means that the number of fleets matched for order i should be minimized to reduce the dispersion rate of matched fleets; This means matching fleets with high priority, i.e., high availability, to the greatest extent possible.

[0079] In the first vehicle matching model, since the objective function is multi-objective programming, the optimal solution cannot be obtained in all situations. When a Pareto optimal solution is obtained, multiple fleet allocation schemes exist. Multiple allocation schemes are not conducive to further ranking, and therefore, it is not conducive to optimizing and recommending the matching scheme. Therefore, the vehicle configuration model can be further optimized.

[0080] In other embodiments, a second vehicle matching model is established, including an objective function and constraints, as follows:

[0081]

[0082]

[0083] In the second vehicle matching model, the constraint *st* is the same as in the first vehicle matching model. A weight *ρ* is introduced into the objective function; this weight is a known value and can be assigned different values ​​as needed. For example, if order *i* is desired to be completed by a single fleet with carrying capacity, let *ρ* = 0; if it is desired to complete the order by combining fleets with the highest idle rates, let *ρ* = 1. In the second vehicle matching model, by introducing the weight *ρ* into the objective function, Pareto optimal solutions can be avoided, thus achieving the goal of order matching and improving matching speed.

[0084] In some other embodiments, based on the idle rate λ jk Calculate the vehicle priority for each vehicle type k in each fleet j. Specifically, it includes:

[0085] The vehicle priority of each vehicle type k is calculated using the following method.

[0086] Vehicle priority calculated using the above method Its value range is [0, 1]. According to the above formula, we know that:

[0087] λ jk When the value is 0, it indicates that there are no available vehicle types k in fleet j, meaning that fleet j does not have the carrying capacity to meet the conditions and cannot appear in the matched fleet combination. Therefore, its priority is... It is also 0.

[0088] λ jk When the value is 1, it means that all vehicles of type k in fleet j are idle. Based on the principle of prioritizing fleets with higher idle rates, this fleet should be matched first. Therefore, its priority is... It is also 1.

[0089] Therefore, prioritizing vehicle type is important. With idle rate λ jk The principle of positive correlation.

[0090] Furthermore, by differentiating the above priority formula, we can obtain: This indicates that the higher the fleet's idle rate, the faster the matching priority increases, ensuring that the goal of prioritizing matching fleets with high idle rates is achieved. Therefore, adopting... The calculation of vehicle type priority means that the relationship between idle rate and priority is not a simple linear one. An increase in idle rate will cause the priority to increase rapidly, which facilitates the quick matching of the target vehicle.

[0091] In some other embodiments, other convex functions representing increasing order can also be used to determine vehicle priority.

[0092] In some other embodiments, to ensure that all vehicles belong to a fleet, when a freight vehicle joins the capacity pool, for example when a fleet registers in the capacity pool, the freight vehicle must choose to open a new fleet or join an existing fleet in the capacity pool.

[0093] In other embodiments, after obtaining a vehicle matching scheme using the vehicle configuration model proposed in this invention, vehicle recommendations can be further made by combining other conditions. For example, recommendations can be made after comprehensively ranking the fleet's historical ratings, reputation levels, etc.

[0094] Figure 2 A schematic diagram of an embodiment of the freight vehicle matching device proposed in this invention is shown. In this embodiment, the capacity pool of the freight vehicles includes multiple fleets, each fleet comprising several vehicles, and each vehicle belonging to one of the fleets. That is, vehicles are assigned to fleets, and numerous fleets converge to form the capacity pool of the freight platform system. The platform system manages the fleets uniformly, efficiently completing vehicle matching and dispatch.

[0095] like Figure 2 As shown, the freight vehicle matching device of this embodiment includes structural modules, the functions of the modules, and the interconnections between them, which are described in detail below:

[0096] The freight vehicle matching device includes:

[0097] Order data receiving module 21 is used to receive data for order i; the data for order i includes the quantity Q of the required vehicle model k. ik .

[0098] Idle rate calculation module 22 is used to calculate the idle rate λ of each vehicle type k in each fleet j in the capacity pool at the time when order i arrives. jk :

[0099] Vehicle type priority calculation module 23 is used to calculate the idle rate λ obtained by idle rate calculation module 22. jk Calculate the vehicle priority for each vehicle type k in each fleet j. Vehicle type priority With idle rate λ jk It satisfies a positive correlation.

[0100] Fleet priority calculation module 24 is used to calculate the vehicle priority of all vehicle types k for each fleet j based on the vehicle type priority calculation module 23. Calculate the fleet priority of fleet j.

[0101] Vehicle configuration model building module 25 is used to establish the decision variable x of fleet j. ij The fleet priority is calculated by the fleet priority calculation module 24. Known M jk and the Q of the order confirmation received by the order data receiving module 21 ik Establish a vehicle configuration model.

[0102] The model solving and vehicle matching module 26 is used to solve the vehicle configuration model established by the vehicle configuration model building module 25, and obtain the decision variable x for each fleet j. ij The value of the decision variable is used to determine the matching fleet, and the matching vehicle is determined based on the vehicle type and idle rate of the matched fleet.

[0103] Where i is the order number; j is the fleet number, j = 1, 2, ..., n, where n is the total number of fleets in the capacity pool; k is the vehicle model number, k = 1, 2, ..., m, where m is the total number of vehicle models in the capacity pool; M jk N represents the number of idle vehicles of model k in fleet j; jkx is the total number of all vehicles of type k in fleet j; ij Let x be the decision variable for vehicle j, taking values ​​of 0 or 1. ij =1 indicates that order i and fleet j are successfully matched, x ij =0 indicates that order i and fleet j were not successfully matched.

[0104] In some other embodiments, the freight vehicle matching device further includes:

[0105] The fleet selection module is used to allow freight vehicles to choose to open a new fleet or join an existing fleet in the capacity pool when joining a capacity pool.

[0106] The freight vehicle matching device with the above structure runs the corresponding software program, performs the corresponding functions, and follows the instructions. Figure 1 The process of the freight vehicle matching method embodiment and other related embodiments involves vehicle matching to achieve the desired result. Figure 1 The corresponding technical effects of the embodiments and other related embodiments.

[0107] Figure 3 A schematic diagram of the structure of an embodiment of the electronic device of the present invention is shown. Figure 3 As shown, the electronic device of this embodiment includes a processor 31, a memory 32, and a computer program 321 stored on the memory 32. The processor 31 is configured to execute the computer program 321 to implement... Figure 1 The embodiments and other embodiments describe freight vehicle matching methods and achieve the technical effects of the corresponding embodiments. The electronic device may be a processor, controller, etc.

[0108] Other embodiments of the present invention also provide a computer storage medium on which a computer program is stored, and when the computer program is executed by a processor, it implements... Figure 1 The embodiments and other embodiments describe freight vehicle matching methods and achieve the technical effects of the corresponding embodiments.

[0109] The aforementioned computer storage media can be implemented using any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The computer storage media can be any available storage medium accessible to general-purpose or special-purpose computers.

[0110] In some embodiments, a computer storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. Both the processor and the storage medium can reside in application-specific integrated circuits (ASICs). Of course, the processor and storage medium can also exist as discrete components in the device.

[0111] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions claimed by the present invention.

Claims

1. A method for matching freight vehicles, characterized in that, The freight vehicle capacity pool comprises multiple fleets, each fleet consisting of several vehicles; the freight vehicle matching method includes: Receive data for order i; the data for order i includes the quantity of the required vehicle model k. ; Calculate the idle rate of each vehicle type k in each fleet j of the capacity pool at the time when order i arrives. : ; According to the idle rate Calculate the vehicle priority for each vehicle type k in each fleet j. The vehicle type priority With the idle rate A positive correlation is satisfied; Based on the vehicle priority of all vehicle types k possessed by each fleet j. Calculate the team priority of team j. ; Based on the decision variables of team j The aforementioned fleet priority The above and the aforementioned Establish a vehicle configuration model; Solve the vehicle configuration model to obtain the decision variables for each fleet j. The value of the decision variable is used to determine the matching fleet; The matching vehicles are determined based on the vehicle type and availability rate of the vehicles in the matched fleet. Where i is the order number; j is the fleet number, j=1,2,…,n, n is the total number of fleets in the capacity pool; k is the vehicle model number, k=1,2,…,m, m is the total number of vehicle models in the capacity pool; Let K be the number of available vehicles of model K in fleet j. Let be the total number of all vehicles of model k in fleet j; Let be the decision variable for vehicle j, taking values ​​of 0 or 1. This indicates that order i and fleet j have been successfully matched. This indicates that order i and fleet j were not successfully matched; Wherein, according to the idle rate Calculate the vehicle priority for each vehicle type k in each fleet j. Specifically, it includes: The priority of each vehicle type k is calculated using the following method. : ; According to the idle rate Calculate the vehicle priority for each vehicle type k in each fleet j. Specifically, it includes: The priority of each vehicle type k is calculated using the following method. : ; The vehicle configuration model includes the following objective function and constraints: ， s.t. ; Alternatively, the vehicle configuration model may include the following objective function and constraints: ， s.t. 。 2. The freight vehicle matching method according to claim 1, characterized in that, The freight vehicle matching method also includes: When a freight vehicle joins the capacity pool, it can choose to open a new fleet or join an existing fleet in the capacity pool.

3. A freight vehicle matching device, characterized in that, The freight vehicle matching device is used to implement the freight vehicle matching method according to claim 1 or 2; the freight vehicle's capacity pool includes multiple fleets, each fleet including several vehicles; the freight vehicle matching device includes: The order data receiving module is used to receive data for order i; the data for order i includes the quantity of the required vehicle model k. ; The idle rate calculation module is used to calculate the idle rate of each vehicle type k in each fleet j in the capacity pool at the time when order i arrives. : ; The vehicle type priority calculation module is used to calculate the vehicle type priority based on the idle rate. Calculate the vehicle priority for each vehicle type k in each fleet j. The vehicle type priority With the idle rate A positive correlation is satisfied; The fleet priority calculation module is used to calculate the vehicle priority based on the vehicle type priority of all vehicle types k owned by each fleet j. Calculate the team priority of team j. ; The vehicle configuration model building module is used to establish the decision variables of fleet j. The aforementioned fleet priority The above and the aforementioned Establish a vehicle configuration model; The model solving and vehicle matching module is used to solve the vehicle configuration model and obtain the decision variables for each fleet j. The value of the decision variable is used to determine the matching fleet, and the matching vehicle is determined based on the vehicle type and idle rate of the vehicle in the matching fleet. Where i is the order number; j is the fleet number, j=1,2,…,n, n is the total number of fleets in the capacity pool; k is the vehicle model number, k=1,2,…,m, m is the total number of vehicle models in the capacity pool; Let K be the number of available vehicles of model K in fleet j. Let be the total number of all vehicles of model k in fleet j; Let be the decision variable for vehicle j, taking values ​​of 0 or 1. This indicates that order i and fleet j have been successfully matched. This indicates that order i and fleet j were not successfully matched.

4. The freight vehicle matching device according to claim 3, characterized in that, The freight vehicle matching device also includes: The fleet selection module is used to allow freight vehicles to choose to open a new fleet or join an existing fleet in the capacity pool when joining the capacity pool.

5. An electronic device comprising a processor, a memory, and a computer program stored in the memory, characterized in that, The processor is configured to execute the computer program to implement the freight vehicle matching method as described in claim 1 or 2.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the freight vehicle matching method as described in claim 1 or 2.

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