A method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways

Abstract

The application discloses a kind of based on wide parallel runway's arrival and departure flight optimization sequencing method, comprising: obtaining constraint variable information;According to the constraint variable information, construct mixed integer linear programming model;Based on the constraint variable information, mixed integer linear programming model is solved using specific algorithm, and the optimal solution of constraint target function in constraint condition definition domain is obtained, and according to the constraint target function optimal solution, arrival and departure flight optimization sequencing is carried out.The application adds the additional constraint relationship of pre-approach flight-post-approach flight, pre-approach flight-post-departure flight, pre-departure flight-post-approach flight, pre-departure flight-post-departure flight, integrates flight arrival and departure joint scheduling problem into optimization constraint model, and introduces queue available position slot intermediate constraint variable, provides global optimal arrival and departure flight optimization sequencing scheme under the condition of meeting real-time requirement, and can be switched in single runway sequencing and multi-runway sequencing by setting parameter variable model.

Description

Technical Field

[0001] This invention relates to the field of airport flight sequencing technology, specifically to a method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways. Background Technology

[0002] Wide-spaced parallel runways refer to runways where the centerline distance between any two parallel runways is greater than 1035 meters. These runways typically operate in a multi-runway independent operation mode, meaning multiple runways can be used simultaneously for flight arrivals and departures, and the arrival and departure traffic flows of different runways are independent of each other. With the increasing volume of civil aviation traffic year by year, major airports both domestically and internationally have begun designing and constructing wide-spaced parallel runways to enable independent parallel instrument approaches and departures during peak hours, further increasing airport operational efficiency. Flight optimization sequencing, on the other hand, determines the optimal takeoff / landing sequence of flights on each runway under certain constraints to improve real-time runway capacity.

[0003] Existing patented technologies mainly involve single-runway arrival and departure flight sequencing, and independent arrival or departure sequencing on wide-spaced parallel runways, primarily including:

[0004] (1) Single-runway arrival and departure flight sequencing method: Small and medium-sized airports generally have only one runway. During peak hours, a large number of flights need to take off and a large number of flights need to land. At this time, continuous arrival and departure flights form a mixed flow of continuous arrivals / departures. In order to increase runway operating efficiency, the first-come-first-served method is generally used to sequence flights. The single-runway flight sequencing operation scenario is relatively simple, and only the impact of the wake turbulence of the preceding and following flights needs to be considered.

[0005] (2) Wide-spaced parallel runway approach sequencing method: The approach sequencing method calculates and optimizes the approach queuing sequence in advance based on airspace parameters and aircraft performance, using a 4D trajectory prediction algorithm and a first-come, first-served strategy. This sequencing scheme only considers the approach traffic flow and does not take into account the interaction of the departure traffic flow, resulting in a less than ideal sequencing effect.

[0006] (3) Wide-spaced parallel runway departure sequencing method: Based on the airline's flight schedule, a first-come, first-served strategy is adopted to optimize the flight departure order and timetable. This sequencing scheme only considers the departure traffic flow and does not take into account the interaction of the arrival traffic flow, resulting in an unsatisfactory sequencing effect.

[0007] (4) Arrival-departure sorting method for wide-spaced parallel runways: At present, there are few sorting methods for arrival-departure of wide-spaced parallel runways. Generally, the first-come-first-served sorting method and the independent optimization sorting method for arrival and departure of flights are still used. However, such methods cannot provide a sorting plan with the maximum throughput or the minimum total flight delay. They can only output a locally optimal sorting scheme. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways, comprising:

[0009] Obtain constraint variable information, which includes the minimum wake vortex separation time for approaching and departing flight pairs based on the time domain;

[0010] A mixed-integer linear programming model is constructed based on the constraint variable information. The mixed-integer linear programming model includes a constraint objective function and constraint conditions.

[0011] A specific algorithm is used to solve the mixed-integer linear programming model to obtain the optimal solution of the constraint objective function within the domain of the constraint conditions, and the arrival and departure flights are optimized and sorted according to the optimal solution of the constraint objective function.

[0012] The step of constructing a mixed-integer linear programming model based on the constraint variable information includes:

[0013] Based on the constraint variable information, construct the wake turbulence interval constraint condition between the preceding and subsequent arrivals to constrain the time interval between the preceding and subsequent arrival flight pairs to be greater than the standard wake turbulence separation interval.

[0014] The preceding approach-following approach wake interval constraint conditions include:

[0015] t p ≥t p-RL +(ya i，p +ya j，p-1 -1)d i，j +(ψa i，r +ψa j，r )d i，j +2ψa j，r-1 (d i，j -D max )-2d i，j

[0016]

[0017] Among them, t p For the planned arrival and departure times of a flight assigned to position slot p, t p-RL Flights are assigned to position slots p-RL Planned entry and exit times, ya i，p For the position slot p of the arriving flight i, select a 0-1 decision variable, ya j,p-1 For the position slot p-1 of the arriving flight j, select a 0-1 decision variable, ψa i,r For the approaching flight i on runway r, select a 0-1 decision variable, ψa j,r For the approaching flight j on runway r, choose a 0-1 decision variable, ψaj,r-1 For the approaching flight j to runway r-1, select a 0-1 decision variable, d i,j D represents the minimum wake separation time for the arrival and departure pairs of the preceding flight i and the subsequent flight j in the time domain. max This represents the maximum wake vortex separation time for approaching and departing flights on the same runway.

[0018] Furthermore, obtaining the constraint variable information includes:

[0019] Collect arrival and departure flight information, including but not limited to the number of flights, flight type, estimated arrival and departure time, and flight plan;

[0020] Obtain control parameters set by the tower controller, including but not limited to flight times, available runways at the airport, and the number of available location slots at the airport;

[0021] Obtain constraint variable information based on the arrival and departure flight information and control parameters;

[0022] The constraint variable information includes the set of arriving and departing flights, the available position slots of the arrival and departure sorting queue, the set of available runways at the airport, the set of estimated arrival and departure times for flights, the number of arriving and departing flights, the maximum delay of arriving and departing flights, the minimum wake separation time of arrival and departure pairs based on the time domain, the maximum displacement offset of flights, and the maximum wake separation time of arrival and departure pairs under the same runway.

[0023] Furthermore, obtaining constraint variable information also includes:

[0024] Define decision variables, including arrival / departure flight-slot selection 0-1 decision variables, arrival / departure flight-runway selection 0-1 decision variables, and the planned arrival / departure time when a flight is assigned to a specific slot.

[0025] When an arriving or departing flight selects a specific location slot, the 0-1 decision variable for the arriving or departing flight-location slot selection is defined as 1, otherwise it is 0.

[0026] When an arriving or departing flight selects a specific runway, the arrival / departure flight-runway selection 0-1 decision variable is defined as 1; otherwise, it is 0.

[0027] Further, the step of constructing a mixed-integer linear programming model based on the constraint variable information includes:

[0028] A constrained objective function is constructed based on the 0-1 decision variables for the arrival and departure flights-position slots, the planned arrival and departure times of flights assigned to specific position slots, and the set of estimated arrival and departure times of flights.

[0029] The constraint objective function includes:

[0030] Where P represents the available slots in the entry / exit sorting queue, and t p For the planned arrival and departure times of flights assigned to position slot p, ya f,p For the position slot p of the arriving flight f, select a 0-1 decision variable, yd f,p For the departing flight f, position slot p is selected as a 0-1 decision variable, Eta f Etd is the set of estimated arrival times for arriving flight f. f Estimate the set of departure times for departing flight f.

[0031] Furthermore, the step of constructing a mixed-integer linear programming model based on the constraint variable information further includes:

[0032] Based on the number of arriving and departing flights and the arrival and departing flight-position slot selection of 0-1 decision variables, a constraint condition for the number of arriving and departing flights is constructed to ensure that the number of flights is equal to the number of scheduled flights during the flight assignment process.

[0033] Based on the 0-1 decision variables for arrival and departure flight-slot selection, a unique constraint condition for the flight selection of slot is constructed to ensure that only one flight takes off and lands in each slot.

[0034] Based on the arrival and departure flight-position slot selection 0-1 decision variables, a unique constraint condition for flight position slot allocation is constructed to constrain the flight allocation of each position slot to a unique runway;

[0035] Based on the arrival and departure flight-position slot selection 0-1 decision variables and arrival and departure flight-runway selection 0-1 decision variables, a unique constraint condition for flight runway selection is constructed to constrain that each flight can only select one runway for take-off and landing during the flight assignment process.

[0036] Based on the arrival and departure flight-position slot selection 0-1 decision variables, the estimated arrival and departure time set of flights, and the maximum delay of arrival and departure flights, flight arrival and departure time window constraints are constructed to constrain any flight's planned arrival and departure time to be greater than the estimated arrival and departure time, and the difference between the planned arrival and departure time and the estimated arrival and departure time does not exceed the maximum delay of arrival and departure flights.

[0037] Based on the maximum displacement offset of the flight and the arrival and departure flight-position slot selection of 0-1 decision variables, a maximum position offset constraint is constructed to constrain the maximum position offset limit of the flight's allowed position change.

[0038] Furthermore, the step of constructing a mixed-integer linear programming model based on the constraint variable information further includes:

[0039] Based on the constraint variable information, construct the wake turbulence interval constraint condition between the preceding arrival and subsequent departure flights to ensure that the time interval between the preceding arrival and subsequent departure flight pairs is greater than the standard wake turbulence separation interval.

[0040] The preceding arrival-following departure wake interval constraint conditions include:

[0041] t p ≥t p-RL +(ya i，p +yd j，p-1 -1)d i，j +(ψa i，r +ψd j，r )d i，j +2ψd j，r-1 (d i，j -D max )-2d i，j

[0042]

[0043] Among them, yd j，p-1 For the departure flight j, position slot p-1, select a 0-1 decision variable, ψd. j，r Choose a 0-1 decision variable ψd for runway r for departing flight j. j，r-1 Choose 0-1 decision variables for departing flight j on runway r-1.

[0044] Furthermore, the step of constructing a mixed-integer linear programming model based on the constraint variable information further includes:

[0045] Based on the constraint variable information, construct the preceding departure-following departure wake interval constraint condition to constrain the time interval between the preceding departure-following departure flight pairs to be greater than the standard wake separation interval.

[0046] The preceding departure-following departure wake interval constraint conditions include:

[0047] t p ≥t p-RL +(yd i，p +yd j，p-1 -1)d i，j +(ψd i，r +ψd j，r )d i，j +2ψd j，r-1 (d i，j -D max )-2d i，j

[0048]

[0049] Among them, yd i，pFor departing flight i, select a 0-1 decision variable p, yd j，p-1 For the departure flight j, position slot p-1, select a 0-1 decision variable, ψd. i，r For departing flight i on runway r, choose a 0-1 decision variable, ψd j，r Choose a 0-1 decision variable ψd for runway r for departing flight j. j，r-1 Choose 0-1 decision variables for departing flight j on runway r-1.

[0050] Furthermore, the step of constructing a mixed-integer linear programming model based on the constraint variable information further includes:

[0051] Based on the constraint variable information, construct the wake turbulence interval constraint condition between the preceding departure and subsequent arrival flights to ensure that the time interval between the preceding departure and subsequent arrival flights is greater than the standard wake turbulence separation interval.

[0052] The preceding departure-subsequent arrival wake interval constraint conditions include:

[0053] t p ≥t p-RL +(yd i，p +ya j，p-1 -1)d i，j +(ψd i，r +ψa j，r )d i，j +2ψa j，r-1 (d i，j -D max )-2d i，j

[0054]

[0055] Among them, yd i,p For departing flights i d The position slot p is selected as a 0-1 decision variable, ψd i,r Choose 0-1 decision variables for departing flight i on runway r.

[0056] Furthermore, the step of solving the mixed-integer linear programming model using a specific algorithm to obtain the optimal solution of the constraint objective function within the domain of the constraint conditions, and then optimizing and ranking flights based on the optimal solution of the constraint objective function, includes:

[0057] A specific algorithm is used to solve the mixed-integer linear programming model to obtain the minimum value of the constraint objective function, thereby obtaining the optimal solution of the constraint objective function within the domain of the constraint conditions;

[0058] The corresponding decision variable values ​​are obtained by minimizing the constraint objective function, and the optimal planned arrival and departure times and arrival and departure runways for each flight are obtained based on the decision variable values.

[0059] Flights are optimized and sorted based on their optimal planned arrival and departure times and arrival / departure runways.

[0060] The specific algorithms include, but are not limited to, branch and bound algorithms, dynamic programming algorithms, and swarm intelligence optimization algorithms.

[0061] The beneficial effects of this invention are reflected in:

[0062] (1) The problem of optimizing the arrival and departure flight schedule for wide-spaced parallel runways is integrated into a single constraint model. Combining the characteristics of the independent operation mode of multiple runways, it is modeled as a mixed integer linear programming problem. The optimal solution can be searched globally in the feasible region to solve the problem of optimizing the original arrival and departure flight schedule under wide-spaced parallel runways. Under the real-time requirement, the globally optimal arrival and departure flight optimization scheduling scheme is output, including the planned arrival time of the flight, the planned departure time of the flight, and the arrival and departure runways of each flight.

[0063] (2) The constructed mixed integer linear programming model can more intuitively quantify the wake interval constraint relationship of each flight under different location slots and runways, and adds additional constraints such as preceding arrival-following arrival flight, preceding arrival-following departure flight, preceding departure-following arrival flight, and preceding departure-following departure flight, as well as consider the impact of wake triangle inequality constraint on the sorting results, covering all operation types of preceding-following flights, making the operation scenario more universal;

[0064] (3) Add the queue available position slot intermediate constraint variable to the constructed mixed integer linear programming model to avoid the dimensionality curse caused by the exponential growth of the number of constraints in the traditional model;

[0065] (4) By setting parameter variable models, it is possible to switch between single-track sorting and multi-track sorting, and output the best combined sorting scheme or FCFS scheme.

[0066] (5) It can be integrated into systems such as air traffic control automation system and tower control automation system to output flight arrival and departure information in real time, improve runway capacity, increase airport operation efficiency, reduce controller workload, and store all prior information and decision variables in the form of one-dimensional and two-dimensional matrices. In terms of engineering, it has advantages such as fast calculation, convenient storage and easy expansion. Attached Figure Description

[0067] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0068] Figure 1 The flowchart illustrates an optimized sorting method for arrival and departure flights based on wide-spaced parallel runways, as provided in this embodiment of the invention. Detailed Implementation

[0069] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0070] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0071] like Figure 1 As shown, a method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways includes:

[0072] S1: Obtain constraint variable information, which includes the minimum wake vortex separation time for approaching and departing flight pairs based on the time domain;

[0073] Specifically, arrival and departure flight information within a certain time range is collected. This information includes, but is not limited to, the number of flights, flight type, estimated arrival and departure times, and flight plans. Simultaneously, control parameters set by tower controllers according to control requirements are obtained. These parameters include, but are not limited to, flight times, available runways, and the number of available airport slots.

[0074] Furthermore, based on the collected arrival and departure flight information and control parameters, constraint variable information is obtained. This constraint variable information includes the arrival and departure flight set F, the available slots in the arrival and departure sorting queue P, the available runway set R, the estimated arrival and departure time set Eta / Etd, and the number of arrival and departure flights N. a / N d Maximum delay of arriving and departing flights (Del) a / Del d Minimum wake separation time d for approach and departure flight pairs based on time domain i,j Maximum flight displacement (mps) and maximum approach / departure flight wake separation time (D) on the same runway. max Among them, the arrival and departure flight set F includes the arrival flight set F. a and departure flight assembly F d F = F a +F d The available runways in the airport set R are independent of each other, and |R| > 1.

[0075] Furthermore, obtaining the constraint variable information also includes defining unknown decision variables, including the 0-1 decision variable ya for arrival / departure flight-position slot selection. f,p / yd f,p Arrival and Departure Flights - Runway Selection 0-1 Decision Variable ψa fa,r / ψd fd,r And the planned arrival and departure times t for flights assigned to specific location slots p The decision variables are assigned values ​​according to the following rules:

[0076] When an arriving or departing flight f selects a specific location slot p, the 0-1 decision variable ya for the arriving or departing flight-location slot selection is defined. f,p / yd f,p It is 1 if it is true, otherwise it is 0.

[0077] When arriving and departing flights f a or f d When selecting a specific runway r, define the 0-1 decision variable ψa for the arrival / departure flight-runway selection. fa,r / ψd fd,r It is 1 if it is true, otherwise it is 0.

[0078] S2: Construct a mixed-integer linear programming model based on the constraint variable information. The mixed-integer linear programming model includes a constraint objective function and constraint conditions.

[0079] Specifically, based on the arrival and departure flight-position slots, select 0-1 decision variables ya. f,p / yd f,p The planned arrival and departure times t for flights assigned to specific location slots p And the estimated arrival and departure times of flights, Eta / Etd, are used to construct a constraint objective function, wherein the constraint objective function obj is:

[0080]

[0081] In the formula, P represents the available slots in the entry / exit sorting queue, and t p For the planned arrival and departure times of flights assigned to position slot p, ya f,p For the position slot p of the arriving flight f, select a 0-1 decision variable, yd f,p For the departing flight f, position slot p is selected as a 0-1 decision variable, Eta f Etd is the set of estimated arrival times for arriving flight f. f Estimate the set of departure times for departing flight f.

[0082] Furthermore, it also includes constructing constraints based on constraint variable information:

[0083] (1) Based on the number of arriving and departing flights Na / N d Arrival and Departure Flights - Position Slot Selection 0-1 Decision Variable ya f，p / yd f，p Establish constraints on the number of arriving or departing flights to ensure that the number of flights equals the number of scheduled flights during the flight assignment process; the constraints on the number of arriving and departing flights are as follows:

[0084]

[0085]

[0086] (2) Select 0-1 decision variables ya based on arrival and departure flight-position slots. f，p / yd f，p A unique constraint is constructed for the selection of flights in each location slot, ensuring that only one flight takes off or lands in each location slot. The unique constraint for selecting flights in each location slot is as follows:

[0087]

[0088] (3) Select 0-1 decision variables ya based on arrival and departure flight-position slots. f，p / yd f，p A unique constraint condition for flight slot allocation is constructed to ensure that each slot has a unique runway allocation; the unique constraint condition for flight slot allocation is as follows:

[0089]

[0090] (4) Select 0-1 decision variables ya based on arrival and departure flight-position slots. f，p / yd f，p The 0-1 decision variable ψa for arrival and departure flights and runway selection. fa，r / ψd fd，r A unique constraint condition for runway selection is constructed to ensure that each flight can only select one runway for takeoff and landing during the flight assignment process; the unique constraint condition for runway selection is as follows:

[0091]

[0092]

[0093] (5) Select 0-1 decision variables ya based on arrival and departure flight-position slots. f，p / yd f，p Estimated arrival and departure times for flights (Eta / Etd) and maximum delays for arrival and departure flights (Del) a / Del dA flight arrival / departure time window constraint is constructed to ensure that the planned arrival / departure time of any flight must be greater than the estimated arrival / departure time, and the difference between the planned arrival / departure time and the estimated arrival / departure time does not exceed the maximum delay of the arriving / departure flight; the flight arrival / departure time window constraint is as follows:

[0094]

[0095]

[0096] (6) Select 0-1 decision variable ya based on the maximum displacement offset of the flight mps and the arrival and departure flight-position slots. f，p / yd f，p A maximum position offset constraint is constructed to limit the maximum position offset allowed for flight changes. When the maximum flight displacement offset mps = 0, the FCFS sorting is achieved. The maximum position offset constraint is as follows:

[0097]

[0098] (7) Construct wake turbulence interval constraints based on constraint variable information to ensure that the time interval between the preceding and subsequent arrival flight pairs is greater than the standard wake separation interval; the preceding and subsequent arrival wake turbulence interval constraints include:

[0099] t p ≥t p-RL +(ya i，p +ya j，p-1 -1)d i，j +(ψa i，r +ψa j，r )d i，j +2ψa j，r-1 (d i，j -D max )-2d i，j

[0100]

[0101] (8) Construct wake turbulence interval constraints based on constraint variable information to ensure that the time interval between the preceding arrival and subsequent departure flight pairs is greater than the standard wake turbulence separation interval; the preceding arrival and subsequent departure wake turbulence interval constraints include:

[0102] t p ≥t p-RL +(ya i，p +yd j，p-1 -1)d i，j +(ψa i，r +ψd j，r )di，j +2ψd j，r-1 (d i，j -D max )-2d i，j

[0103]

[0104] (9) Construct the wake turbulence interval constraint condition between the preceding departure and the subsequent departure based on the constraint variable information, so that the time interval between the preceding departure and the subsequent departure flight pair must be greater than the standard wake turbulence separation interval.

[0105] The preceding departure-following departure wake interval constraint conditions include:

[0106] t p ≥t p-RL +(yd i，p +yd j，p-1 -1)d i，j +(ψd i，r +ψd j，r )d i，j +2ψd j，r-1 (d i，j -D max )-2d i，j

[0107]

[0108] (10) Construct wake turbulence interval constraints based on constraint variable information to constrain the time interval between the preceding departure and subsequent arrival flight pairs to be greater than the standard wake turbulence separation interval; the preceding departure-subsequent arrival wake turbulence interval constraints include:

[0109] t p ≥t p-RL +(yd i，p +ya j，p-1 -1)d i，j +(ψd i，r +ψa j，r )d i，j +2ψa j，r-1 (d i，j -D max )-2d i，j

[0110]

[0111] Preferably, the meanings of each constraint (1) to (10) are explained as follows:

[0112] N a N represents the number of arriving flights. dFor the number of departing flights, Eta f Etd is the set of estimated arrival times for flight f. f For the set of estimated departure times for flight f, Del a For the maximum delay of arriving flights, Del d This represents the maximum delay for departing flights;

[0113] ya f，p For the position slot p of the arriving flight f, select a 0-1 decision variable, yd f，p Choose a 0-1 decision variable for position slot p of departing flight f; ya fd，p For the incoming flight f a Position slot p is selected as a 0-1 decision variable, yd fd，p For departing flights f d The position slot p is selected as a 0-1 decision variable; ya i，p For the position slot p of the arriving flight i, select a 0-1 decision variable, ya j，p-1 Choose a 0-1 decision variable for position slot p-1 of arriving flight j; yd i，p For departing flight i, select a 0-1 decision variable p, yd j，p-1 Choose a 0-1 decision variable for slot p-1 of departing flight j;

[0114] ψa fa，r For the incoming flight f a Runway r selects 0-1 decision variables, ψd fd，r For departing flights f d Runway r is chosen as a 0-1 decision variable, ψa i，r For the approaching flight i on runway r, select a 0-1 decision variable, ψa j，r For the approaching flight j on runway r, choose a 0-1 decision variable, ψa j，r-1 Choose 0-1 decision variables for approaching flight j on runway r-1; ψd i，r For departing flight i on runway r, choose a 0-1 decision variable, ψd j，r Choose a 0-1 decision variable ψd for runway r for departing flight j. j，r-1 Choose 0-1 decision variables for departing flight j on runway r-1;

[0115] t p For the planned arrival and departure times of a flight assigned to position slot p, t p-RL Flights are assigned to position slots p-RL The planned entry and exit times, where RL is a constant, and the traversal value [1,P] represents the position slot of the position slot P preceding the position of RL;

[0116] d i,j D represents the minimum wake separation time for the arrival and departure pairs of the preceding flight i and the subsequent flight j in the time domain.max ρ represents the maximum wake vortex separation time for approaching and departing flights on the same runway, and ρ represents the number of slots in which the flight moves forward or backward.

[0117] Based on the constructed objective function and constraints, a mixed-integer linear programming model is constructed so that the problem of optimizing the arrival and departure flight ordering of wide-spaced parallel runways can be integrated into a single constrained model, and the globally optimal arrival and departure flight ordering scheme can be output.

[0118] S3: Solve the mixed-integer linear programming model using a specific algorithm to obtain the optimal solution of the constraint objective function within the domain of the constraint conditions, and optimize the sorting of arriving and departing flights based on the optimal solution of the constraint objective function;

[0119] Specifically, a specific algorithm is used to solve the mixed-integer linear programming model to obtain the minimum value of the constraint objective function, thereby obtaining the optimal solution of the constraint objective function within the domain of the constraint conditions. Preferably, the specific algorithm includes, but is not limited to, branch and bound algorithms, dynamic programming algorithms, and swarm intelligence optimization algorithms, and is not limited thereto.

[0120] Furthermore, the values ​​of each decision variable are obtained based on the minimum value of the constraint objective function. The optimal planned arrival and departure times and runways for each flight are then determined based on these decision variable values. Finally, the flights are optimized and ranked according to their optimal planned arrival and departure times and the runways for each flight.

[0121] The optimized flight sorting method based on wide-spaced parallel runways described in this invention has the following beneficial effects:

[0122] (1) The problem of optimizing the arrival and departure flight schedule of wide-spaced parallel runways is integrated into a constraint model. Combined with the characteristics of the independent operation mode of multiple runways, it is modeled as a mixed integer linear programming problem. It can search for the optimal solution globally in the feasible region, solve the problem of optimizing the original arrival and departure flight schedule under wide-spaced parallel runways, and output the flight plan arrival time, flight plan departure time and the arrival and departure runways of each flight. Under the real-time requirement, it outputs the globally optimal arrival and departure flight optimization scheduling scheme.

[0123] (2) The constructed mixed integer linear programming model can more intuitively quantify the wake interval constraint relationship of each flight under different location slots and runways, and adds additional constraints such as preceding arrival-following arrival flight, preceding arrival-following departure flight, preceding departure-following arrival flight, and preceding departure-following departure flight, as well as consider the impact of wake triangle inequality constraint on the sorting results, covering all operation types of preceding-following flights, making the operation scenario more universal;

[0124] (3) Add the queue available position slot intermediate constraint variable to the constructed mixed integer linear programming model to avoid the dimensionality curse caused by the exponential growth of the number of constraints in the traditional model;

[0125] (4) By setting parameter variable models, it is possible to switch between single-track sorting and multi-track sorting, and output the best combined sorting scheme or FCFS scheme.

[0126] (5) It can be integrated into systems such as air traffic control automation system and tower control automation system to output flight arrival and departure information in real time, improve runway capacity, increase airport operation efficiency, reduce controller workload, and store all prior information and decision variables in the form of one-dimensional and two-dimensional matrices. In terms of engineering, it has advantages such as fast calculation, convenient storage and easy expansion.

[0127] 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 them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways, characterized in that, include: Obtain constraint variable information, which includes the minimum wake vortex separation time for approaching and departing flight pairs based on the time domain; A mixed-integer linear programming model is constructed based on the constraint variable information. The mixed-integer linear programming model includes a constraint objective function and constraint conditions. A specific algorithm is used to solve the mixed-integer linear programming model to obtain the optimal solution of the constraint objective function within the domain of the constraint conditions, and the arrival and departure flights are optimized and sorted according to the optimal solution of the constraint objective function. The step of constructing a mixed-integer linear programming model based on the constraint variable information includes: Based on the constraint variable information, construct the wake turbulence interval constraint condition between the preceding and subsequent arrivals to constrain the time interval between the preceding and subsequent arrival flight pairs to be greater than the standard wake turbulence separation interval. The preceding approach-following approach wake interval constraint conditions include: t p ≥t p-RL +(of i，p +of j，p-1 -1)d i，j +(ψa i，r +ψa j，r )d i，j +2ψa j，r-1 (d i，j -D max )-2d i，j Among them, t p For the planned arrival and departure times of a flight assigned to position slot p, t p-RL For the scheduled arrival and departure times of flights assigned to position slot p-RL, ya i,p For the position slot p of the arriving flight i, select a 0-1 decision variable, ya j,p-1 For the position slot p-1 of the arriving flight j, select a 0-1 decision variable, ψa i,r For the approaching flight i on runway r, select a 0-1 decision variable, ψa j,r For the approaching flight j on runway r, choose a 0-1 decision variable, ψa j,r-1 For the approaching flight j to runway r-1, select a 0-1 decision variable, d i,j D represents the minimum wake separation time for the arrival and departure pairs of the preceding flight i and the subsequent flight j in the time domain. max This represents the maximum wake vortex separation time for approaching and departing flights on the same runway.

2. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 1, characterized in that, The process of obtaining constraint variable information includes: Collect arrival and departure flight information, including but not limited to the number of flights, flight type, estimated arrival and departure time, and flight plan; Obtain control parameters set by the tower controller, including but not limited to flight times, available runways at the airport, and the number of available location slots at the airport; Obtain constraint variable information based on the arrival and departure flight information and control parameters; The constraint variable information includes the set of arriving and departing flights, the available position slots of the arrival and departure sorting queue, the set of available runways at the airport, the set of estimated arrival and departure times for flights, the number of arriving and departing flights, the maximum delay of arriving and departing flights, the minimum wake separation time of arrival and departure pairs based on the time domain, the maximum displacement offset of flights, and the maximum wake separation time of arrival and departure pairs under the same runway.

3. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 2, characterized in that, The process of obtaining constraint variable information also includes: Define decision variables, including arrival / departure flight-slot selection 0-1 decision variables, arrival / departure flight-runway selection 0-1 decision variables, and the planned arrival / departure time when a flight is assigned to a specific slot. When an arriving or departing flight selects a specific location slot, the 0-1 decision variable for the arriving or departing flight-location slot selection is defined as 1, otherwise it is 0. When an arriving or departing flight selects a specific runway, the arrival / departure flight-runway selection 0-1 decision variable is defined as 1; otherwise, it is 0.

4. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 3, characterized in that, The step of constructing a mixed-integer linear programming model based on the constraint variable information includes: A constrained objective function is constructed based on the 0-1 decision variables for the arrival and departure flights-position slots, the planned arrival and departure times of flights assigned to specific position slots, and the set of estimated arrival and departure times of flights. The constraint objective function includes: Where P represents the available slots in the entry / exit sorting queue, and t p For the planned arrival and departure times of flights assigned to position slot p, ya f,p For the position slot p of the arriving flight f, select a 0-1 decision variable, yd f,p For the departing flight f, position slot p is selected as a 0-1 decision variable, Eta f Etd is the set of estimated arrival times for arriving flight f. f Estimate the set of departure times for departing flight f.

5. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 4, characterized in that, The step of constructing a mixed-integer linear programming model based on the constraint variable information further includes: Based on the number of arriving and departing flights and the arrival and departing flight-position slot selection of 0-1 decision variables, a constraint condition for the number of arriving and departing flights is constructed to ensure that the number of flights is equal to the number of scheduled flights during the flight assignment process. Based on the 0-1 decision variables for arrival and departure flight-slot selection, a unique constraint condition for the flight selection of slot is constructed to ensure that only one flight takes off and lands in each slot. Based on the arrival and departure flight-position slot selection 0-1 decision variables, a unique constraint condition for flight position slot allocation is constructed to constrain the flight allocation of each position slot to a unique runway; Based on the arrival and departure flight-position slot selection 0-1 decision variables and arrival and departure flight-runway selection 0-1 decision variables, a unique constraint condition for flight runway selection is constructed to constrain that each flight can only select one runway for take-off and landing during the flight assignment process. Based on the arrival and departure flight-position slot selection 0-1 decision variables, the estimated arrival and departure time set of flights, and the maximum delay of arrival and departure flights, flight arrival and departure time window constraints are constructed to constrain any flight's planned arrival and departure time to be greater than the estimated arrival and departure time, and the difference between the planned arrival and departure time and the estimated arrival and departure time does not exceed the maximum delay of arrival and departure flights. Based on the maximum displacement offset of the flight and the arrival and departure flight-position slot selection of 0-1 decision variables, a maximum position offset constraint is constructed to constrain the maximum position offset limit of the flight's allowed position change.

6. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 4, characterized in that, The step of constructing a mixed-integer linear programming model based on the constraint variable information further includes: Based on the constraint variable information, construct the wake turbulence interval constraint condition between the preceding arrival and subsequent departure flights to ensure that the time interval between the preceding arrival and subsequent departure flight pairs is greater than the standard wake turbulence separation interval. The preceding arrival-following departure wake interval constraint conditions include: the p ≥t p-RL +(yes i，p +yd j，p-1 -1)d i，j +(ψa i，r +ψd j，r )is i，j +2ψd j，r-1 (is i，j -IS max )-2d i，j Among them, yd j，p-1 For the departure flight j, position slot p-1, select a 0-1 decision variable, ψd. j，r Choose a 0-1 decision variable ψd for runway r for departing flight j. j，r-1 Choose 0-1 decision variables for departing flight j on runway r-1.

7. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 4, characterized in that, The step of constructing a mixed-integer linear programming model based on the constraint variable information further includes: Based on the constraint variable information, construct the preceding departure-following departure wake interval constraint condition to constrain the time interval between the preceding departure-following departure flight pairs to be greater than the standard wake separation interval. The preceding departure-following departure wake interval constraint conditions include: the p ≥t p-RL +(yd i，p +yd j，p-1 -1)d i，j +(ψd i，r +ψd j，r )is i，j +2ψd j，r-1 (is i，j -IS max )-2d i，j Among them, yd i，p For departing flight i, select a 0-1 decision variable p, yd j，p-1 For the departure flight j, position slot p-1, select a 0-1 decision variable, ψd. i，r For departing flight i on runway r, choose a 0-1 decision variable, ψd j，r Choose a 0-1 decision variable ψd for runway r for departing flight j. j，r-1 Choose 0-1 decision variables for departing flight j on runway r-1.

8. The method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to claim 4, characterized in that, The step of constructing a mixed-integer linear programming model based on the constraint variable information further includes: Based on the constraint variable information, construct the wake turbulence interval constraint condition between the preceding departure and subsequent arrival flights to ensure that the time interval between the preceding departure and subsequent arrival flights is greater than the standard wake turbulence separation interval. The preceding departure-subsequent arrival wake interval constraint conditions include: the p ≥t p-RL +(yd i，p +yes j，p-1 -1)d i，j +(ψd i，r +ψa j，r )is i，j +2ψa j，r-1 (is i，j -IS max )-2d i，j Among them, yd i,p For departing flights i d The position slot p is selected as a 0-1 decision variable, ψd i,r Choose 0-1 decision variables for departing flight i on runway r.

9. A method for optimizing the sequencing of arrival and departure flights based on wide-spaced parallel runways according to any one of claims 5-8, characterized in that, The process of solving the mixed-integer linear programming model using a specific algorithm to obtain the optimal solution of the constraint objective function within the domain of the constraint conditions, and then optimizing and ranking flights based on the optimal solution of the constraint objective function, includes: A specific algorithm is used to solve the mixed-integer linear programming model to obtain the minimum value of the constraint objective function, thereby obtaining the optimal solution of the constraint objective function within the domain of the constraint conditions; The corresponding decision variable values ​​are obtained by minimizing the constraint objective function, and the optimal planned arrival and departure times and arrival and departure runways for each flight are obtained based on the decision variable values. Flights are optimized and sorted based on their optimal planned arrival and departure times and arrival / departure runways. The specific algorithms include, but are not limited to, branch and bound algorithms, dynamic programming algorithms, and swarm intelligence optimization algorithms.

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