A method and system for rapidly dispatching aircraft takeoff, landing and parking at medium and large airports

Abstract

The present invention discloses a method and system for quickly scheduling aircraft takeoff, landing and parking at medium and large airports. It introduces a "distillation" strategy for large-scale complex problems. Through precise extraction and simplification, it first obtains the exact mathematical solution of the corresponding small-scale problem, and on this basis, determines the optimal parking scheduling strategy for rescue aircraft. On this basis, through a detailed study of the "diffusion" process of the problem, a high-quality approximate solution framework for the original problem is constructed, that is, a high-precision solution sequence for the coordinated operation of aircraft takeoff, landing and parking is formed. Finally, an innovative "landing priority" strategy is adopted to transform this solution sequence into a practical and high-quality solution, which comprehensively covers the takeoff, landing and parking requirements of all rescue aircraft and generates a detailed general scheduling table. Therefore, the method proposed in the present invention successfully circumvents the tedious process of lengthy iterative optimization in large-scale real-world problems, and provides a new and efficient solution for the efficient scheduling of disaster relief airports.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and relates to a method and system for rapidly dispatching aircraft take-off, landing and parking at medium and large airports. Background Art

[0002] In the context of emergency rescue efforts fueled by frequent natural disasters and various emergencies, research into methods for rapidly dispatching and transferring rescue supplies at medium- and large-sized airports has become particularly urgent and important. Faced with emergency rescue missions, airports need to respond quickly, efficiently dispatch aircraft takeoffs and landings, and rationally arrange parking spaces to ensure that relief supplies can reach the disaster area as quickly as possible, buying valuable time to save lives and reduce disaster losses. This research not only helps improve airports' emergency response capabilities and operational efficiency, but is also directly linked to the success of rescue operations, and is of great significance for protecting the lives and property of people in disaster-stricken areas. By continuously optimizing and improving aircraft takeoffs, landings, and parking methods, medium- and large-sized airports can provide more solid and reliable support for future emergency rescue missions, contributing wisdom and strength to saving more lives and reducing losses.

[0003] Existing technical solutions primarily focus on airlines' daily operations. The general process is as follows: Airlines develop flight plans based on market trends and their own capacity, and submit them to the Civil Aviation Administration of China for approval. Once approved, the flight plan becomes the core basis for subsequent aircraft scheduling and crew arrangements. In practice, all flights strictly adhere to this established schedule. However, this model ignores the immediate impact that market dynamics and unexpected events can have on flight operations.

[0004] Current technical solutions generally rely on known flight schedules (defined as the takeoff and landing times of all aircraft) to construct the optimal runway and parking position combination. In the absence of pre-defined flight schedules, this traditional approach is clearly inadequate for effectively coordinating the actions of various departments to maximize overall rescue efficiency.

[0005] At the algorithmic level, existing technologies often rely on traditional metaheuristics. While these algorithms can solve problems to a certain extent, they typically require lengthy iterative optimization cycles to arrive at a satisfactory solution. When faced with the massive amounts of data generated by medium- to large-scale airports, traditional algorithms struggle to deliver high-quality solutions in a timely manner. This shortcoming is particularly acute when responding to emergencies that require a rapid response. Summary of the Invention

[0006] The purpose of the present invention is to solve the problems in the prior art and to provide a method and system for quickly scheduling aircraft take-off, landing and parking at medium and large airports.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] The present invention proposes a method for rapidly scheduling aircraft takeoff, landing, and parking at medium and large airports, comprising:

[0009] Obtaining a reduced airport input data set, and building an airport scheduling model based on the reduced airport input data set;

[0010] Solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft;

[0011] Based on the optimal parking results of all aircraft, the total operation time of all aircraft parking is calculated, and the total operation time is sorted to obtain a solution sequence. The optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

[0012] Preferably, obtaining the reduced airport input data set comprises:

[0013] The airport input data set S includes: the number of runways r, the number of parking spaces g, the total number of rescue aircraft n, and each aircraft A i Time required to land on the runway i , each aircraft A i Time required for takeoff on the runway d i , and the loading and unloading time p required for each aircraft at the parking stand i ; where i = 1, 2, ..., n;

[0014] Let the scale scaling factor be θ and the numerical scaling factor be τ; the reduced airport input data set S' is obtained as follows: the number of runways at the airport r'=r / θ, the number of parking spaces at the airport g'=g / θ, the total number of rescue aircraft n'=n / θ, the type of aircraft h i , the time required for each aircraft to land on the runway i '=l i / τ, the time d required for each aircraft to take off on the runway i '=d i / τ, and the loading and unloading time p required for each aircraft at the parking stand i '=p i / τ; where i'=1, 2, ..., n / θ, θ is an integer greater than 1, and the numerical scaling factor τ is l i d i 、p i The greatest common factor of .

[0015] Preferably, the airport scheduling model is constructed based on the reduced airport input data set as follows:

[0016]

[0017]

[0018] Among them, g' is the number of parking spaces at the airport, n' is the total number of rescue aircraft, l i ' is the time required for each aircraft to land on the runway, d i ' is the time required for each aircraft to take off on the runway, p i ' is the loading and unloading time required for each aircraft at the parking stand; i',j' It is a 0-1 variable. When it is 1, it means that the aircraft is A. i’ Park at parking space G j’ Otherwise, it is 0; C max The time when the last aircraft takes off and leaves under this scheduling plan is the time required for all aircraft to complete takeoff, landing and parking.

[0019] Preferably, the airport scheduling model is solved to obtain the optimal scheduling solution of the model and the optimal parking result of all aircraft, specifically:

[0020] Obtain the set of all 0-1 variables y in the optimal solution of the airport scheduling model after reduction Y'={y i’j’ |i'=1,2,…,n';j'=1,2,…,g'};Calculate the set Y of all 0-1 variables y in the optimal or approximately optimal solution of the original problem from the set Y',

[0021] If y ij =1, then aircraft A i Park at parking space G j Otherwise, it means aircraft A i Not parked at parking space G j The optimal parking results for all aircraft are obtained.

[0022] Preferably, the total parking operation time of all aircraft is calculated based on the optimal parking results of all aircraft, the total operation time is sorted to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy, specifically:

[0023] For any parking space G j , calculate the total operating time t of all aircraft parked on it i The sum of Among them, the total operation time t i =l i +di +p i , l i For each aircraft A i Time required to land on the runway, d i For each aircraft A i Time required for takeoff on the runway, p i The time required for loading and unloading each aircraft at the parking stand;

[0024] According to the total operation time of all aircraft t i sum j Order all parking spaces G from large to small j Sort by

[0025] Each parking space G j For all aircraft parked at the parking position, the length of their parking time p i All aircraft are sorted from small to large to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

[0026] The present invention proposes a system for rapidly dispatching aircraft takeoff, landing, and parking at medium and large airports, comprising:

[0027] a model building module, the model building module being used to obtain a reduced airport input data set and to build an airport scheduling model based on the reduced airport input data set;

[0028] A parking result acquisition module is used to solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft;

[0029] The take-off and landing result acquisition module is used to calculate the total parking operation time of all aircraft based on the optimal parking results of all aircraft, sort the total operation time to obtain a solution sequence, and obtain the optimal take-off and landing results of all aircraft from the solution sequence according to the landing priority strategy.

[0030] Preferably, the airport scheduling model is constructed based on the reduced airport input data set as follows:

[0031]

[0032] Among them, g' is the number of parking spaces at the airport, n' is the total number of rescue aircraft, l i ' is the time required for each aircraft to land on the runway, d i ' is the time required for each aircraft to take off on the runway, p i ' is the loading and unloading time required for each aircraft at the parking stand; i',j' It is a 0-1 variable. When it is 1, it means that the aircraft is A. i’Park at parking space G j’ Otherwise, it is 0; C max The time when the last aircraft takes off and leaves under this scheduling plan is the time required for all aircraft to complete takeoff, landing and parking.

[0033] Preferably, the total parking operation time of all aircraft is calculated based on the optimal parking results of all aircraft, the total operation time is sorted to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy, specifically:

[0034] For any parking space G j , calculate the total operating time t of all aircraft parked on it i The sum of Among them, the total operation time t i =l i +d i +p i , l i For each aircraft A i Time required to land on the runway, d i is the time required for takeoff, p i The time required for loading and unloading each aircraft at the parking stand;

[0035] According to the total operation time of all aircraft t i sum j Order all parking spaces G from large to small j Sort by

[0036] Each parking space G j For all aircraft parked at the parking position, the length of their parking time p i All aircraft are sorted from small to large to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

[0037] A terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, steps of a method for rapidly dispatching aircraft takeoff, landing, and parking at medium and large airports are implemented.

[0038] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for rapidly scheduling aircraft takeoff, landing, and parking at medium and large airports.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention proposes a method for quickly scheduling aircraft takeoff, landing and parking at medium and large airports, which successfully overcomes the difficulty of medium and large airports in quickly and accurately providing high-quality scheduling solutions in disaster relief emergency situations, and effectively overcomes the inherent limitations of traditional metaheuristic algorithms in solution efficiency. A "distillation" strategy for large-scale complex problems is introduced. Through precise refinement and simplification, the exact mathematical solution of the corresponding small-scale problem is first obtained. Based on this, the optimal parking scheduling strategy for rescue aircraft is further derived and determined. On this basis, the present invention continues to deepen the analysis and successfully constructs a high-quality approximate solution framework for the original problem through a detailed study of the "diffusion" process of the problem, that is, a set of high-precision solution sequences for the coordinated operation of aircraft takeoff, landing and parking is formed. Finally, the present invention adopts an innovative "landing priority" strategy to transform this solution sequence into a practical and high-quality solution, which comprehensively covers the takeoff, landing and parking needs of all rescue aircraft and generates a detailed master scheduling table. In summary, this invention not only cleverly applies the principle of mathematical exact solutions to ensure the high quality of aircraft scheduling solutions in a scientific and rigorous manner, but also achieves a major breakthrough in traditional methods at the methodological level, successfully avoiding the tedious process of lengthy iterative optimization in large-scale real-world problems, and providing a new and efficient solution for the efficient scheduling of disaster relief airports.

[0041] This paper proposes a system for rapidly scheduling aircraft takeoffs, landings, and parking at medium- to large-sized airports. By dividing the system into a model-building module, a parking result acquisition module, and a takeoff and landing result acquisition module, the system obtains optimal takeoff and landing results for all aircraft, as well as optimal parking results for all aircraft. This system enables rapid scheduling of aircraft takeoffs, landings, and parking at medium- to large-sized airports. The modular design makes each module independent, facilitating unified management of all modules. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 This is a flow chart of the method for rapidly scheduling aircraft takeoff, landing and parking at medium and large airports according to the present invention.

[0044] Figure 2 This is a schematic diagram of the aircraft take-off, landing and parking process of the present invention.

[0045] Figure 3 Schematic diagram of the process of solving the problems of "distillation" and "diffusion" in the present invention.

[0046] Figure 4 The figure is a comparison chart of the solution quality of the present invention and the classic algorithm under different runway configurations.

[0047] Figure 5 The figure is a comparison of the solution time of the present invention and the classic algorithm under different runway configurations.

[0048] Figure 6 This is a system diagram for rapidly dispatching aircraft takeoff, landing, and parking at medium and large airports according to the present invention.

[0049] Figure 7 The figure is a schematic structural diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0050] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0051] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0052] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition or explanation in subsequent drawings.

[0053] In the description of the embodiments of the present invention, it should be noted that if the terms "upper," "lower," "horizontal," "inner," etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the inventive product is typically placed when in use. These terms are merely for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0054] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0055] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0056] The present invention is described in further detail below with reference to the accompanying drawings:

[0057] The present invention proposes a method for rapidly dispatching aircraft takeoff, landing and parking at medium and large airports, such as Figure 1 As shown, the following steps are included:

[0058] S1. Obtain a reduced airport input data set, and build an airport scheduling model based on the reduced airport input data set;

[0059] The obtained reduced airport input data set is specifically:

[0060] The airport input data set S includes: the number of runways r, the number of parking spaces g, the total number of rescue aircraft n, and each aircraft A i Time required to land on the runway i , each aircraft A i Time required for takeoff on the runway d i , and the loading and unloading time p required for each aircraft at the parking stand i ; where i = 1, 2, ..., n;

[0061] Let the scale scaling factor be θ and the numerical scaling factor be τ; the reduced airport input data set S' is obtained as follows: the number of runways at the airport r'=r / θ, the number of parking spaces at the airport g'=g / θ, the total number of rescue aircraft n'=n / θ, the type of aircraft h i , the time required for each aircraft to land on the runway i '=l i / τ, the time d required for each aircraft to take off on the runway i '=d i / τ, and the loading and unloading time p required for each aircraft at the parking stand i '=p i / τ; where i = 1, 2, ..., n / θ, θ is an integer greater than 1, and the numerical scaling factor τ is l i d i 、p i The greatest common factor of .

[0062] The airport scheduling model is constructed based on the reduced airport input data set as follows:

[0063]

[0064] Among them, g' is the number of parking spaces at the airport, n' is the total number of rescue aircraft, l i ' is the time required for each aircraft to land on the runway, d i ' is the time required for each aircraft to take off on the runway, p i ' is the loading and unloading time required for each aircraft at the parking stand; i',j' It is a 0-1 variable. When it is 1, it means that the aircraft is A. i’ Park at parking space G j’ Otherwise, it is 0; C max The time when the last aircraft takes off and leaves under this scheduling plan is the time required for all aircraft to complete takeoff, landing and parking.

[0065] S2. Solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft;

[0066] The airport scheduling model is solved to obtain the optimal scheduling solution of the model and the optimal parking result of all aircraft, specifically:

[0067] Obtain the set of all 0-1 variables y in the optimal solution of the airport scheduling model Y'={y i’j’ |i'=1,2,…,n';j'=1,2,…,g'};Calculate the set Y of all 0-1 variables y in the optimal or approximately optimal solution of the original problem from the set Y',

[0068] If y ij =1, then aircraft A i Park at parking space G j Otherwise, it means aircraft A i Not parked at parking space G j The optimal parking results for all aircraft are obtained.

[0069] S3. Calculate the total parking operation time of all aircraft based on the optimal parking results of all aircraft, sort the total operation time to obtain a solution sequence, and obtain the optimal takeoff and landing results of all aircraft according to the landing priority strategy based on the solution sequence.

[0070] The total parking operation time of all aircraft is calculated based on the optimal parking results of all aircraft, and the total operation time is sorted to obtain a solution sequence. The optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy, specifically:

[0071] For any parking space G j , calculate the total operating time t of all aircraft parked on it i sum j =∑t i ; Among them, the total operation time t i =l i +d i +p i , l i For each aircraft A i Time required to land on the runway, d i is the time required for takeoff, p i The time required for loading and unloading each aircraft at the parking stand;

[0072] According to the total operation time of all aircraft t i sum j Order all parking spaces G from large to small j Sort by

[0073] Each parking space G j For all aircraft parked at the parking position, the length of their parking time p i From small to large, for all aircraft A i The solution sequence is obtained by sorting, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

[0074] The method is described in detail below with reference to the accompanying drawings:

[0075] Step 1: Summarize and organize the input data. Figure 2 , is a schematic diagram of the aircraft take-off, landing and parking process. The airport input data set S includes: the number of runways r, the number of parking spaces g, the total number of rescue aircraft n, and each aircraft A i Time required to land on the runway i , each aircraft A i Time required for takeoff on the runway d i , and the loading and unloading time p required for each aircraft at the parking stand i , (i=1,2,…,n).

[0076] Step 2: Reduce the problem size. Let the scale scaling factor be θ (θ is an integer greater than 1), the numerical scaling factor be τ (τ is l i d i 、p i The reduced airport input data set S' is obtained as follows: the number of runways r'=r / θ, the number of parking spaces g'=g / θ, the total number of rescue aircraft n'=n / θ, the type of each aircraft h i, the time required for each aircraft to land on the runway can be inferred from the aircraft type and other information i '=l i / τ, the time d required for each aircraft to take off on the runway i '=d i / τ, and the loading and unloading time p required for each aircraft at the parking stand i '=p i / τ, (i'=1,2,…,n / θ).

[0077] Step 3: Accurately solve the narrowed problem. Use CPLEX software to accurately solve the problem of the airport input data set S'. The input airport scheduling model is as follows:

[0078]

[0079] Step 4: Obtain the optimal or approximately optimal scheduling solution for the original problem. From step 3, we can obtain the set of all 0-1 variables y in the optimal solution of the small-scale problem, Y'={y i’j’ |i'=1,2,…,n';j'=1,2,…,g'}. Calculate the set Y of all 0-1 variables y in the optimal or approximately optimal solution of the original problem from Y',

[0080] Step 5: Obtain the optimal or approximately optimal solution for aircraft parking. ij =1, then aircraft A i Park at parking space G j Otherwise, it means aircraft A i Not parked at parking space G j Thus, the parking plan for all aircraft can be obtained.

[0081] Step 6: Obtain the optimal or approximately optimal solution sequence for aircraft takeoff and landing.

[0082] For any parking space G j , calculate the total operating time of all aircraft parked on it (t i =l i +d i +p i ), sum j =∑t i ;

[0083] According to sum j Order all parking spaces G from large to small j Sort by

[0084] Each parking space G j For all aircraft parked at the stand, the length of their parking time (pi ), from small to large for all aircraft A i Sort by

[0085] Generate the solution sequence for aircraft takeoff and landing according to the following process:

[0086]

[0087] Step 7: Obtain the solution from the solution sequence according to the landing priority strategy. The specific process is as follows: Input: List of aircraft to be dispatched L l (Includes information and input sequence of all rescue aircraft)

[0088] Output: The scheduling of all rescue aircraft and the total rescue time (i.e. C max )

[0089] Setting parameters: Number of landed aircraft n in =0, the number of aircraft that have taken off n out =0L l The first g aircraft landed in succession, updating the runway R i The earliest available time is ra i

[0090] Update L l :L l Delete the first g aircraft

[0091] The aircraft that have completed landing are arranged into parking spaces in turn, and the G of each parking space is updated. i The earliest available time ga i

[0092]

[0093]

[0094] See also Figure 3 , which is a schematic diagram of the solution process for the "distillation" and "diffusion" problems. Process (a) corresponds to step 2, process (b) corresponds to steps 3 and 4, and process (c) corresponds to steps 5, 6, and 7.

[0095] See also Figure 4 , is a comparison of the solution quality of the algorithm proposed by the present invention and the classic algorithm for airports with different numbers of runways. The horizontal axis is the name of each comparison algorithm; the vertical axis is a box plot, showing the difference in solution quality between each algorithm and the best performing algorithm (unit: percentage). Figure 4 (a) shows the performance of each algorithm when the number of runways is 2. Figure 4 (b) shows the performance of each algorithm when the number of runways is 3. Figure 4(c) shows the performance of each algorithm when the number of runways is 4. Figure 4 (d) in the figure shows the performance of each algorithm when the number of runways is 5.

[0096] See also Figure 5 , is a comparison of the computation time of the algorithm proposed by the present invention and the classical algorithm at airports with different numbers of runways. The horizontal axis is the name of each comparison algorithm; the vertical axis is a box plot showing the computation time (unit: seconds) of each algorithm. Figure 5 (a) shows the performance of each algorithm when the number of runways is 2. Figure 5 (b) shows the performance of each algorithm when the number of runways is 3. Figure 5 (c) shows the performance of each algorithm when the number of runways is 4. Figure 5 (d) in the figure shows the performance of each algorithm when the number of runways is 5.

[0097] Example 2

[0098] The present invention proposes a system for rapidly dispatching aircraft takeoff, landing and parking at medium and large airports. Figure 6 As shown, including:

[0099] a model building module, the model building module being used to obtain a reduced airport input data set and to build an airport scheduling model based on the reduced airport input data set;

[0100] The obtained reduced airport input data set is specifically:

[0101] The airport input data set S includes: the number of runways r, the number of parking spaces g, the total number of rescue aircraft n, and each aircraft A i Time required to land on the runway i , each aircraft A i Time required for takeoff on the runway d i , and the loading and unloading time p required for each aircraft at the parking stand i ; where i = 1, 2, ..., n;

[0102] Let the scale scaling factor be θ and the numerical scaling factor be τ; the reduced airport input data set S' is obtained as follows: the number of runways at the airport r'=r / θ, the number of parking spaces at the airport g'=g / θ, the total number of rescue aircraft n'=n / θ, the type of aircraft h i , the time required for each aircraft to land on the runway i '=l i / τ, the time d required for each aircraft to take off on the runway i '=d i / τ, and the loading and unloading time p required for each aircraft at the parking stand i '=pi / τ; where i = 1, 2, ..., n / θ, θ is an integer greater than 1, and the numerical scaling factor τ is l i d i 、p i The greatest common factor of .

[0103] The airport scheduling model is constructed based on the reduced airport input data set as follows:

[0104]

[0105] Among them, g' is the number of parking spaces at the airport, n' is the total number of rescue aircraft, l i ' is the time required for each aircraft to land on the runway, d i ' is the time required for each aircraft to take off on the runway, p i ' is the loading and unloading time required for each aircraft at the parking stand; i',j' It is a 0-1 variable. When it is 1, it means that the aircraft is A. i’ Park at parking space G j’ Otherwise, it is 0; C max The time when the last aircraft takes off and leaves under this scheduling plan is the time required for all aircraft to complete takeoff, landing and parking.

[0106] A parking result acquisition module is used to solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft;

[0107] The airport scheduling model is solved to obtain the optimal scheduling solution of the model and the optimal parking result of all aircraft, specifically:

[0108] Obtain the set of all 0-1 variables y in the optimal solution of the airport scheduling model Y'={y i’j’ |i'=1,2,…,n';j'=1,2,…,g'};Calculate the set Y of all 0-1 variables y in the optimal or approximately optimal solution of the original problem from the set Y',

[0109] If y ij =1, then aircraft A i Park at parking space G j Otherwise, it means aircraft A i Not parked at parking space G j The optimal parking results for all aircraft are obtained.

[0110] The take-off and landing result acquisition module is used to calculate the total parking operation time of all aircraft based on the optimal parking results of all aircraft, sort the total operation time to obtain a solution sequence, and obtain the optimal take-off and landing results of all aircraft from the solution sequence according to the landing priority strategy.

[0111] The total parking operation time of all aircraft is calculated based on the optimal parking results of all aircraft, and the total operation time is sorted to obtain a solution sequence. The optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy, specifically:

[0112] For any parking space G j , calculate the total operating time t of all aircraft parked on it i sum j =∑t i ; Among them, the total operation time t i =l i +d i +p i , l i For each aircraft A i Time required to land on the runway, d i is the time required for takeoff, p i The time required for loading and unloading each aircraft at the parking stand;

[0113] According to the total operation time of all aircraft t i sum j Order all parking spaces G from large to small j Sort by

[0114] Each parking space G j For all aircraft parked at the parking position, the length of their parking time p i From small to large, for all aircraft A i The solution sequence is obtained by sorting, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

[0115] Example 3

[0116] See also Figure 7 As shown, the present invention also provides an electronic device 100 for a method of quickly dispatching aircraft takeoff, landing and parking at medium and large airports; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and capable of running on the at least one processor 102, and at least one communication bus 104.

[0117] The memory 101 can be used to store the computer program 103. The processor 102 implements the method steps for quickly scheduling aircraft takeoff, landing, and parking at medium and large airports as described in Example 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data (such as audio data) created based on the use of the electronic device 100. In addition, the memory 101 can include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device.

[0118] The at least one processor 102 may 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. The processor 102 may be a microprocessor or any conventional processor, etc. The processor 102 is the control center of the electronic device 100 and connects various parts of the entire electronic device 100 using various interfaces and lines.

[0119] The memory 101 in the electronic device 100 stores a plurality of instructions for implementing a method for rapidly scheduling aircraft takeoff, landing, and parking at a medium or large airport. The processor 102 can execute the plurality of instructions to implement:

[0120] Obtaining a reduced airport input data set, and building an airport scheduling model based on the reduced airport input data set;

[0121] Solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft;

[0122] Based on the optimal parking results of all aircraft, the total operation time of all aircraft parking is calculated, and the total operation time is sorted to obtain a solution sequence. The optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

[0123] Example 4

[0124] If the module / unit integrated in the electronic device 100 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0125] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0127] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0128] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for rapidly dispatching aircraft takeoff, landing and parking at medium and large airports, characterized in that: include: Obtaining a reduced airport input data set, and building an airport scheduling model based on the reduced airport input data set; Solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft; Based on the optimal parking results of all aircraft, the total parking operation time of all aircraft is calculated, the total operation time is sorted to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy; The obtained reduced airport input data set is specifically: Get the airport input dataset S Includes: Number of runways at the airport r , the number of parking spaces at the airport g , the total number of rescue aircraft n , each aircraft A i Time required to land on the runway l i , each aircraft A i Time required to take off on the runway d i , and the loading and unloading time required for each aircraft at the parking stand p i ;in, i =1,2, …, n ; Let the scaling factor be θ , the numerical scaling factor is τ ; Get the reduced airport input dataset S’ is: Number of runways at the airport r’ = r / θ , the number of parking spaces at the airport g’ = g / θ , the total number of rescue aircraft n’ = n / θ , aircraft type h i , the time required for each aircraft to land on the runway l i ’ = l i / τ , the time required for each aircraft to take off on the runway d i ’ = d i / τ , and the loading and unloading time required for each aircraft at the parking stand p i ’ = p i / τ ;in, i’ =1,2, …, n / θ , θ An integer greater than 1, a numerical scaling factor τ for l i 、 d i 、 p i The greatest common factor of ; The airport scheduling model is constructed based on the reduced airport input data set as follows: in, It is a 0-1 variable. When it is 1, it means the aircraft A i’ Parked at the parking space G j’ Otherwise, it is 0; C max The time when the last aircraft takes off and leaves under this scheduling plan is the time required for all aircraft to complete takeoff, landing and parking.

2. The method for rapidly dispatching aircraft takeoff, landing and parking at medium and large airports according to claim 1, characterized in that: The airport scheduling model is solved to obtain the optimal scheduling solution of the model and the optimal parking result of all aircraft, specifically: Obtain all 0-1 variables in the optimal solution of the airport scheduling model after reduction y Collection Y’ ={ y i’j’ | i’= 1, 2, … , n’ ; j’ = 1, 2, … , g’ }; By the collection Y’ Calculate all 0-1 variables in the optimal or approximately optimal solution to the original problem y Collection Y , ={ y ij | i = 1, 2, … , n ; j = 1, 2, … , g }; if y ij =1, then the aircraft A i Parked at the parking space G j On; otherwise , indicating the aircraft A i Not parked at a parking space G j The optimal parking results for all aircraft are obtained.

3. The method for rapidly dispatching aircraft takeoff, landing and parking at medium and large airports according to claim 1, characterized in that: The total parking operation time of all aircraft is calculated based on the optimal parking results of all aircraft, and the total operation time is sorted to obtain a solution sequence. The optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy, specifically: For any parking space G j , calculate the total operating time of all aircraft parked on it t i The sum of ; Among them, the total operation time t i = l i + d i + p i , l i For each aircraft A i The time required to land on the runway, d i For each aircraft A i Time required to take off from the runway, p i The loading and unloading time required for each aircraft at the parking stand, n The total number of rescue aircraft; By total operating time of all aircraft t i The sum of sum j All parking spaces in descending order G j Sort by Each parking space G j For all aircraft parked at the stand, the length of their parking time p i p l All aircraft are sorted from small to large to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

4. A system for rapid scheduling of aircraft takeoff, landing and parking at medium and large airports, characterized by: include: a model building module, the model building module being used to obtain a reduced airport input data set and to build an airport scheduling model based on the reduced airport input data set; A parking result acquisition module is used to solve the airport scheduling model to obtain the optimal scheduling solution of the model and obtain the optimal parking results for all aircraft; a takeoff and landing result acquisition module, which is used to calculate the total parking operation time of all aircraft based on the optimal parking results of all aircraft, sort the total operation time to obtain a solution sequence, and obtain the optimal takeoff and landing results of all aircraft from the solution sequence according to the landing priority strategy; The obtained reduced airport input data set is specifically: Get the airport input dataset S Includes: Number of runways at the airport r , the number of parking spaces at the airport g , the total number of rescue aircraft n , each aircraft A i Time required to land on the runway l i , each aircraft A i Time required to take off on the runway d i , and the loading and unloading time required for each aircraft at the parking stand p i ;in, i =1,2, …, n ; Let the scaling factor be θ , the numerical scaling factor is τ ; Get the reduced airport input dataset S’ is: Number of runways at the airport r’ = r / θ , the number of parking spaces at the airport g’ = g / θ , the total number of rescue aircraft n’ = n / θ , aircraft type h i , the time required for each aircraft to land on the runway l i ’ = l i / τ , the time required for each aircraft to take off on the runway d i ’ = d i / τ , and the loading and unloading time required for each aircraft at the parking stand p i ’ = p i / τ ;in, i’ =1,2, …, n / θ , θ An integer greater than 1, a numerical scaling factor τ for l i 、 d i 、 p i The greatest common factor of ; The airport scheduling model is constructed based on the reduced airport input data set as follows: in, It is a 0-1 variable. When it is 1, it means the aircraft A i’ Parked at the parking space G j’ Otherwise, it is 0; C max The time when the last aircraft takes off and leaves under this scheduling plan is the time required for all aircraft to complete takeoff, landing and parking.

5. The system for rapid scheduling of aircraft takeoff, landing and parking at medium and large airports according to claim 4 is characterized in that: The total parking operation time of all aircraft is calculated based on the optimal parking results of all aircraft, and the total operation time is sorted to obtain a solution sequence. The optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy, specifically: For any parking space G j , calculate the total operating time of all aircraft parked on it t i The sum of ; Among them, the total operation time t i = l i + d i + p i , l i For each aircraft A i The time required to land on the runway, d i The time required for takeoff, p i The loading and unloading time required for each aircraft at the parking stand, n The total number of rescue aircraft; By total operating time of all aircraft t i The sum of sum j All parking spaces in descending order G j Sort by Each parking space G j For all aircraft parked at the stand, the length of their parking time p i All aircraft are sorted from small to large to obtain a solution sequence, and the optimal take-off and landing results of all aircraft are obtained from the solution sequence according to the landing priority strategy.

6. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for rapidly scheduling aircraft takeoff, landing and parking at medium and large airports as described in any one of claims 1 to 3 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for rapidly scheduling aircraft takeoff, landing and parking at medium and large airports as described in any one of claims 1 to 3 are implemented.

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