Scheduling method, system and equipment for air-ground combined transportation

Abstract

The invention discloses a scheduling method, system and equipment for air-ground combined transport, and the method comprises the steps: firstly obtaining vehicle transport capacity information, flight dynamic information and order information, and the order information comprises an order departure place and collection time, and an order destination and arrival time; according to the vehicle transport capacity information, the flight dynamic information and the order information, determining an order segmented transportation mode, the segmented transportation mode including air transportation and land transportation; a scheduling model is constructed in a segmented mode according to an order segmented transportation mode, and air-ground combined transportation is carried out according to a result of the scheduling model; according to the invention, the order information is obtained, air transportation and land transportation are modeled in a segmented manner according to the actual business scene of the order information, and different transportation modes are coupled, so that the logistics efficiency is improved, and the scheduling is more accurate and reasonable.

Description

Technical Field

[0001] The present invention relates to the field of logistics and transportation technology, and in particular to a scheduling method, system and equipment for land-air combined transportation. Background Art

[0002] With the advancement of information technology, long-distance transportation is becoming increasingly widespread, requiring the coordination of air and land transportation. Consequently, an increasing number of airlines and logistics companies are adopting intelligent scheduling systems. Leveraging technologies such as big data and artificial intelligence, these systems can automatically analyze logistics demand, optimize route planning, and schedule flights, significantly improving scheduling efficiency and accuracy. Intelligent scheduling algorithms and technologies have emerged throughout the logistics management process. Their core goal is to optimize logistics network operations by rationally allocating cargo and vehicle resources, thereby improving logistics efficiency. Currently, several traditional algorithms are commonly used for flight and vehicle scheduling in aviation logistics: genetic algorithms, tabu search algorithms, simulated annealing algorithms, ant colony algorithms, and particle swarm algorithms. These algorithms use a series of heuristic rules or simulate specific natural processes to search the solution space, finding near-optimal solutions within a reasonable timeframe. Most current technologies fall under the heuristic category of optimization algorithms, and their efficiency varies across different business scenarios. Heuristic algorithms also involve numerous hyperparameters, significantly impacting their performance. Summary of the Invention

[0003] The present invention provides a scheduling method, system and equipment for land-air transport, which models air and land transport in sections according to actual business scenarios, improves logistics efficiency and makes scheduling more accurate and reasonable.

[0004] To solve the above technical problems, the present invention provides a scheduling method for land-air transport, comprising:

[0005] Obtain vehicle capacity information, flight dynamic information, and order information, wherein the order information includes the order origin and pickup time, as well as the order destination and delivery time;

[0006] Determine the method of segmented transportation of the order based on vehicle capacity information, flight dynamic information, and order information, where segmented transportation methods include air transportation and land transportation;

[0007] The scheduling model is constructed in sections according to the order segment transportation method, and land-air combined transportation is carried out based on the results of the scheduling model.

[0008] Optionally, methods for determining order segmentation based on order origin and pickup time, and order destination and delivery time include:

[0009] Based on the collection time, delivery time and flight dynamic information, Yen's algorithm is used to select the shortest air route;

[0010] Obtain the shortest land transport route based on the order origin, order destination and vehicle capacity information.

[0011] Optionally, the shortest land transport route includes the order origin-origin shipping station route, the origin shipping station-departure airport route, the arrival airport-arrival freight station route and the arrival freight station-order destination route.

[0012] Optionally, the segmented construction of the scheduling model for road-air transport in accordance with the segmented transportation method of the order includes segmented construction of the scheduling model and constraints for the order origin-origin shipping station route, the origin shipping station-departure airport route, the arrival airport-arrival cargo station route and the arrival cargo station-order destination route, wherein the constraints include vehicle allocation constraints, time constraints and refrigeration constraints.

[0013] Optionally, the objective functions of the originating cargo station-departure airport route and the arrival airport-arrival cargo station route are:

[0014]

[0015] The cost function is:

[0016] Among them, K represents the order that needs to participate in the multi-point delivery; R k represents the optional routes for order k; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;q k Indicates the weight of goods for order k; represents the cost of vehicle v assigned to the point-to-point delivery route; represents the basic cost of vehicle v; Indicates the unit price of weight, exceeding the basic weight u v After that, the freight per kg; u v represents the basic load of vehicle v; y rv It is a Boolean variable indicating whether vehicle v uses the serial route r.

[0017] Optionally, the vehicle allocation constraints include:

[0018] One vehicle is assigned to one order:

[0019]

[0020] The vehicle travels along a connecting route:

[0021]

[0022] Vehicle usage:

[0023]

[0024] Vehicle load:

[0025]

[0026] Where: V r represents the available vehicles v of the connecting route r; M represents a natural number; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;y rv is a Boolean variable indicating whether vehicle v uses the serial line r; q k represents the weight of goods for order k; Q v represents the maximum capacity of vehicle v.

[0027] Optionally, the time constraint includes:

[0028] Departure time of vehicle v from the city freight station:

[0029]

[0030]

[0031] Time for vehicle v to arrive at the airport:

[0032]

[0033] Vehicle v must arrive at the departure airport no later than the flight time assigned to the order:

[0034]

[0035] The time when vehicle v leaves and arrives at the airport:

[0036]

[0037] Order delivery cannot be later than the order product aging time:

[0038]

[0039] in: represents the transportation time and loading and unloading time of order k from the origin to the city freight station, k∈K; l k represents the expected pickup time for order k in the door-to-port segment; represents the cargo loading / unloading time of order k at the corresponding city freight station; Indicates that vehicle V arrives at city freight station w k moment; δ represents the relaxation coefficient of the land transport section; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ; Indicates the city freight station w on the connecting line r k’ Is the successor node of the city freight station w k ; Indicates the time when the vehicle leaves the airport; Indicates that from the city freight station w k Time to airport a; Indicates the city freight station w on the connecting line r k Whether the successor node is airport a; Indicates that order k corresponds to airport A k Cargo transit time; sT k represents the departure time of the flight assigned to order k; eT k represents the arrival time of the flight assigned to order k; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; represents the transportation time and loading and unloading time of order k from the city freight station to the delivery destination, k∈K; a k Indicates the latest delivery deadline for order k.

[0040] Optionally, the refrigeration constraint conditions include:

[0041]

[0042] The latest arrival time of the output order at the city freight station:

[0043]

[0044] Among them: VC v It is of Boolean type, indicating whether the vehicle v is a refrigerated truck; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;OC kIt is a Boolean type, which determines whether the order k is for refrigerated goods; sT k represents the departure time of the flight assigned to order k; Indicates that order k corresponds to airport A k cargo transit time; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading and unloading time between k , k∈K; represents the loading and unloading time of order k at the corresponding city freight station.

[0045] To solve the above technical problems, an embodiment of the present invention further provides a scheduling system for land-air transport, comprising:

[0046] An information acquisition module, configured to acquire vehicle capacity information, flight dynamic information, and order information, wherein the order information includes the order origin and pickup time, as well as the order destination and delivery time;

[0047] A segmented transportation determination module is used to determine the segmented transportation method of the order based on vehicle capacity information, flight dynamic information, and order information, where the segmented transportation methods include air transportation and land transportation;

[0048] The land-air intermodal transport scheduling module is used to construct a scheduling model in sections according to the order segmentation method, and carry out land-air intermodal transport based on the results of the scheduling model.

[0049] To solve the above technical problems, an embodiment of the present invention further provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the scheduling method for land-air transport.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention discloses a scheduling method, system and equipment for land-air combined transport. The method first obtains vehicle capacity information, flight dynamic information and order information, wherein the order information includes the order origin and collection time as well as the order destination and delivery time; determines the mode of segmented transportation of the order based on the vehicle capacity information, flight dynamic information and order information, wherein the segmented transportation mode includes air transportation and land transportation; constructs a scheduling model in segments according to the mode of segmented transportation of the order, and performs land-air combined transport based on the results of the scheduling model; the present invention obtains order information, models air transportation and land transportation in segments according to the actual business scenarios of the order information, couples different transportation modes, improves logistics efficiency, and makes scheduling more accurate and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the present invention, the following briefly introduces the drawings used in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0053] Figure 1 is a flow chart of a scheduling method for land-air transport provided by an embodiment of the present invention;

[0054] Figure 2 1 is a schematic structural diagram of a dispatching system for land-air transport provided by an embodiment of the present invention;

[0055] Figure 3 This is a structural block diagram of a terminal device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0057] See also Figure 1 , is a structural diagram of a first embodiment of a data collector provided by the present invention, wherein the scheduling method for land-air transport comprises steps S1 to S3:

[0058] S1. Obtain vehicle capacity information, flight dynamic information, and order information, wherein the order information includes the order origin and pickup time, as well as the order destination and delivery time;

[0059] S2. Determine a method for segmented transportation of the order based on vehicle capacity information, flight dynamic information, and order information, where the segmented transportation method includes air transportation and land transportation;

[0060] S3. Construct a scheduling model in sections according to the order segment transportation method, and carry out land-air combined transportation based on the results of the scheduling model.

[0061] In one implementation, a mixed integer linear model is used based on China Southern Airlines Logistics' current land-air intermodal transport scenarios. Technically, a model is built for a specific business scenario, and the optimal solution can be found within that scenario. Business-wise, the system automatically calculates multiple available routes based on existing flight routes, warehouses, cargo terminals, origins, and destinations, taking into account factors such as capacity, cost, and timeliness. Routing and dispatch orders are automatically generated to ensure optimal timeliness and cost, thereby improving logistics efficiency, effectively scheduling and utilizing resources, and increasing business volume.

[0062] In one embodiment, the method of determining the segmented transportation of an order based on the order origin and pickup time and the order destination and delivery time includes:

[0063] Based on the collection time, delivery time and flight dynamic information, Yen's algorithm is used to select the shortest air route;

[0064] It should be noted that in the embodiments of the present invention, Yen's algorithm is an efficient algorithm for finding K disjoint shortest paths in a graph. During the generation and pruning of shortest paths, information from the previous shortest path can be used to guide the search for the next shortest path, avoiding repeated calculations and improving computational efficiency.

[0065] Obtain the shortest land transport route based on the order origin, order destination and vehicle capacity information.

[0066] In one embodiment, the shortest land transport route includes an order origin-origin shipping station route, an origin shipping station-departure airport route, an arrival airport-arrival freight station route, and an arrival freight station-order destination route.

[0067] It should be noted that in the embodiment of the present invention, the standard process of logistics transportation is: order origin-origin shipping station-origin airport-arrival airport-arrival cargo station-order destination; considering the four dimensions of time, space, cost, and efficiency, the entire process is divided into three sections: customer-city cargo station, city cargo station-airport, and airport-airport. An optimization model is established for each section. Among them, the customer-city cargo station and city cargo station-airport models are based on the results of the airport-airport model. (1) Flight scheduling model (airport-airport model): considering constraints such as flight capacity and order time constraints, flights are allocated to orders with the comprehensive cost time as the goal, and the airport loading and unloading time, the detour time of the land transport vehicle, and the slack time are considered. (2) City cargo station to airport scheduling model (city cargo station-airport): according to the flight departure / arrival time, order shipment / deadline delivery time, etc., time constraints are established, and the vehicle load constraints are considered. With the total cost minimization goal such as comprehensive transportation distance cost, appropriate connecting point routes and vehicles are allocated to orders. (3) Door-to-city freight station scheduling model (customer-city freight station): Based on the city freight station to airport scheduling model, the latest arrival time of the corresponding goods at the city freight station, transportation time and other information are obtained to establish the time constraints of the door-to-city freight station section, and the vehicle load constraints are taken into account. With the goal of minimizing the total cost, appropriate delivery vehicles are allocated to the orders.

[0068] In one embodiment, the segmented construction of the scheduling model for road-air transport in accordance with the segmented transportation of orders includes segmented construction of the scheduling model and constraints for the order origin-origin shipping station route, the origin shipping station-departure airport route, the arrival airport-arrival cargo station route, and the arrival cargo station-order destination route, wherein the constraints include vehicle allocation constraints, time constraints, and refrigeration constraints.

[0069] It should be noted that, in the embodiment of the present invention, the originating freight station-departure airport route and the arrival airport-arrival freight station route support business scenarios that require point-to-point transportation. Orders correspond one-to-one to city freight stations, and city freight stations have multiple point-to-point routes connecting different airports. This section model selects the point-to-point route between the originating airport determined by the port-to-port section and the city freight station corresponding to the order, allocates vehicles to the order, and meets time constraints.

[0070] In one embodiment, the objective functions of the origin station-departure airport route and the arrival airport-arrival cargo terminal route are:

[0071]

[0072] The cost function is:

[0073] Among them, K represents the order that needs to participate in the multi-point delivery; R k represents the optional routes for order k; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;q k Indicates the weight of goods for order k; represents the cost of vehicle v assigned to the point-to-point delivery route; represents the basic cost of vehicle v; Indicates the unit price of weight, exceeding the basic weight u v After that, the freight per kg; u v represents the basic load of vehicle v; y rv It is a Boolean variable indicating whether vehicle v uses the serial route r.

[0074] In one embodiment, the vehicle assignment constraints include:

[0075] One vehicle is assigned to one order:

[0076]

[0077] The vehicle travels along a connecting route:

[0078]

[0079] Vehicle usage:

[0080]

[0081] Vehicle load:

[0082]

[0083] Where: V r represents the available vehicles v of the connecting route r; M represents a natural number; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;y rv is a Boolean variable indicating whether vehicle v uses the serial line r; q k represents the weight of goods for order k; Q v represents the maximum capacity of vehicle v.

[0084] In one embodiment, the time constraints include:

[0085] Departure time of vehicle v from the city freight station:

[0086]

[0087] Time for vehicle v to arrive at the airport:

[0088]

[0089] Vehicle v must arrive at the departure airport no later than the flight time assigned to the order:

[0090]

[0091] The time when vehicle v leaves and arrives at the airport:

[0092]

[0093] Order delivery cannot be later than the order product aging time:

[0094]

[0095] in: represents the transportation time and loading and unloading time of order k from the origin to the city freight station, k∈K; l k represents the expected pickup time for order k in the door-to-port segment; represents the cargo loading / unloading time of order k at the corresponding city freight station; Indicates that vehicle V arrives at city freight station w k moment; δ represents the relaxation coefficient of the land transport section; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ; Indicates the city freight station w on the connecting line r k’ Is the successor node of the city freight station w k ; Indicates the time when the vehicle leaves the airport; Indicates that from the city freight station w k Time to airport a; Indicates the city freight station w on the connecting line r k Whether the successor node is airport a; Indicates that order k corresponds to airport A k Cargo transit time; sT k represents the departure time of the flight assigned to order k; eT k represents the arrival time of the flight assigned to order k; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; represents the transportation time and loading and unloading time of order k from the city freight station to the delivery destination, k∈K; a k Indicates the latest delivery deadline for order k.

[0096] In one embodiment, the refrigeration constraints include:

[0097]

[0098] The latest arrival time of the output order at the city freight station:

[0099]

[0100] Among them: VC v It is of Boolean type, indicating whether the vehicle v is a refrigerated truck; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;OC k It is a Boolean type, which determines whether the order k is for refrigerated goods; sT k represents the departure time of the flight assigned to order k; Indicates that order k corresponds to airport A k cargo transit time; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading and unloading time between k , k∈K; represents the loading and unloading time of order k at the corresponding city freight station.

[0101] Based on the above method embodiments, the present invention provides corresponding system embodiments.

[0102] To solve the above technical problems, see Figure 2 , an embodiment of the present invention further provides a scheduling system for land-air transport, comprising:

[0103] Information acquisition module 21, used to obtain vehicle capacity information, flight dynamic information and order information, wherein the order information includes the order origin and collection time, as well as the order destination and delivery time;

[0104] The segmented transport determination module 22 is used to determine the segmented transport method of the order based on the order origin and collection time as well as the order destination and delivery time. The segmented transport methods include air transport and land transport.

[0105] The land-air transport scheduling module 23 is used to construct a scheduling model in sections according to the order segment transportation method, and perform land-air transport according to the results of the scheduling model.

[0106] It should be noted that in the embodiments of the present invention, the modeling is based on the actual business scenarios of China Southern Airlines Logistics and is carried out in a segmented manner according to the order. Route splitting is automatically achieved, and after splitting, a model is established for each business scenario: the entire logistics transportation process is a door-to-door multimodal transport scheduling problem, and the different scheduling segments are coupled with each other. The solution space for this type of multimodal scheduling problem is large, and the problem scale grows exponentially with the number of orders. In addition, the problem is also subject to many complex constraints, including time window constraints and capacity constraints. Therefore, in order to obtain a suboptimal solution within an acceptable time, the idea of problem decomposition is adopted to automatically decompose the multi-segment scheduling of freight orders into shipping resource scheduling and land transportation resource scheduling.

[0107] It should be noted that the cargo flight scheduling optimization system provided in an embodiment of the present invention is used to execute all the process steps of a cargo flight scheduling optimization method in the above embodiment. The working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0108] The embodiment of the present invention further provides a terminal device, such as Figure 3 FIG2 is a block diagram of a preferred embodiment of a terminal device provided by the present invention. The terminal device includes a processor 31, a memory 32, and a computer program stored in the memory 32 and configured to be executed by the processor 31. When the processor 31 executes the computer program, it implements the cargo flight scheduling optimization method described in any of the above embodiments.

[0109] In addition, an embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the cargo flight scheduling optimization method described in any of the above embodiments.

[0110] When the processor 31 executes the computer program, the steps in the above-mentioned embodiment of the cargo flight scheduling optimization method are implemented, for example: Figure 1 Alternatively, when the processor 31 executes the computer program, the functions of each module in the above-mentioned embodiment of the cargo flight scheduling optimization system are realized, such as Figure 2 The functions of each module of the cargo flight scheduling optimization system are shown.

[0111] Preferably, the computer program can be divided into one or more modules / units, which are stored in the memory 32 and executed by the processor 31 to implement the present invention. The one or more modules / units can be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0112] The processor 31 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor, or the processor 31 can be any conventional processor. The processor 31 is the control center of the terminal device, and uses various interfaces and lines to connect the various parts of the terminal device.

[0113] The memory 32 mainly includes a program storage area and a data storage area. The program storage area can store an operating system, at least one application required for a function, and the data storage area can store related data. In addition, the memory 32 can be a high-speed random access memory or a non-volatile memory such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, or a flash card. Alternatively, the memory 32 can be other volatile solid-state memory devices.

[0114] It should be noted that the above terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that Figure 3 The structural block diagram shown is only an example of the structure of the terminal device and does not constitute a structural limitation of the terminal device. The terminal device may include more or fewer components than shown in the figure, or a combination of certain components, or different components.

[0115] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A scheduling method for land-air transport, characterized in that: The following steps are involved: Obtain vehicle capacity information, flight dynamic information, and order information, wherein the order information includes the order origin and pickup time, as well as the order destination and delivery time; Determine the method of segmented transportation of the order based on vehicle capacity information, flight dynamic information, and order information, where segmented transportation methods include air transportation and land transportation; The scheduling model is constructed in sections according to the order segment transportation method, and land-air combined transportation is carried out based on the results of the scheduling model.

2. A dispatching method for land-air transport according to claim 1, characterized in that: Methods for determining order segmentation based on vehicle capacity information, flight dynamics information, and order information include: Based on the collection time, delivery time and flight dynamic information, Yen's algorithm is used to select the shortest air route; Obtain the shortest land transport route based on the order origin, order destination and vehicle capacity information.

3. The method for dispatching land-air transport according to claim 2, characterized in that: The shortest land transport routes include the order origin-origin shipping station route, the origin shipping station-departure airport route, the arrival airport-arrival freight station route and the arrival freight station-order destination route.

4. The method for dispatching land-air transport according to claim 3, characterized in that: The method of constructing a scheduling model in sections according to the order segmented transportation method for road-air intermodal transport includes constructing a scheduling model and constraints for the order origin-origin shipping station route, the origin shipping station-departure airport route, the arrival airport-arrival cargo station route, and the arrival cargo station-order destination route; wherein the constraints include vehicle allocation constraints, time constraints, and refrigeration constraints.

5. The method for dispatching land-air transport according to claim 4, characterized in that: The objective functions of the origin station-departure airport route and the arrival airport-arrival cargo terminal route are: The cost function is: Among them, K represents the order that needs to participate in the multi-point delivery; R k represents the optional routes for order k; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;q k Indicates the weight of goods for order k; represents the cost of vehicle v assigned to the point-to-point delivery route; represents the basic cost of vehicle v; Indicates the unit price of weight, exceeding the basic weight u v After that, the freight per kg; u v represents the basic load of vehicle v; y rv It is a Boolean variable indicating whether vehicle v uses the serial route r.

6. A dispatching method for land-air transport according to claim 5, characterized in that: The vehicle allocation constraints include: One vehicle is assigned to one order: The vehicle travels along a connecting route: Vehicle usage: Vehicle load: Where: V r represents the available vehicles v of the connecting route r; M represents a natural number; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;y rv is a Boolean variable indicating whether vehicle v uses the serial line r; q k represents the weight of goods for order k; Q v represents the maximum capacity of vehicle v.

7. The method for dispatching land-air transport according to claim 5, characterized in that: The time constraints include: Departure time of vehicle v from the city freight station: Time for vehicle v to arrive at the airport: Vehicle v must arrive at the departure airport no later than the flight time assigned to the order: The time when vehicle v leaves and arrives at the airport: Order delivery cannot be later than the order product aging time: in: represents the transportation time and loading and unloading time of order k from the origin to the city freight station, k∈K; l k represents the expected pickup time for order k in the door-to-port segment; represents the cargo loading / unloading time of order k at the corresponding city freight station; Indicates that vehicle V arrives at city freight station w k moment; δ represents the relaxation coefficient of the land transport section; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ; Indicates the city freight station w on the connecting line r k’ Is the successor node of the city freight station w k ; Indicates the time when the vehicle leaves the airport; Indicates that from the city freight station w k Time to airport a; Indicates the city freight station w on the connecting line r k Whether the successor node is airport a; Indicates that order k corresponds to airport A k Cargo transit time; sT k represents the departure time of the flight assigned to order k; eT k represents the arrival time of the flight assigned to order k; Indicates that the connecting point line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; represents the transportation time and loading and unloading time of order k from the city freight station to the delivery destination, k∈K; a k Indicates the latest delivery deadline for order k.

8. The method for dispatching land-air transport according to claim 5, characterized in that: The cold storage constraints include: The latest arrival time of the output order at the city freight station: Among them: VC v It is of Boolean type, indicating whether the vehicle v is a refrigerated truck; is a Boolean variable, which is 1 if the delivery vehicle v of order k is connected with the line r, otherwise it is 0 r∈R k ,v∈V r ;OC k It is a Boolean type, which determines whether the order k is for refrigerated goods; sT k represents the departure time of the flight assigned to order k; Indicates that order k corresponds to airport A k cargo transit time; Indicates that the connecting line is between the airport and the cargo terminal w k The transportation time and loading / unloading time between k , k∈K; It represents the cargo loading / unloading time of order k at the corresponding city freight station.

9. A dispatching system for land-air transport, characterized in that: include: An information acquisition module, configured to acquire vehicle capacity information, flight dynamic information, and order information, wherein the order information includes the order origin and pickup time, as well as the order destination and delivery time; A segmented transportation determination module is used to determine the segmented transportation method of the order based on vehicle capacity information, flight dynamic information, and order information, where the segmented transportation methods include air transportation and land transportation; The land-air intermodal transport scheduling module is used to construct a scheduling model in sections according to the order segmentation method, and carry out land-air intermodal transport based on the results of the scheduling model.

10. A terminal device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a scheduling method for land-air transport according to any one of claims 1 to 8 is implemented.

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