A Cooperative Optimization Method for Flight Takeoff and Landing in Multi-runway Airport Based on Hybrid Genetic Algorithm

Abstract

The invention discloses a collaborative optimization method for flight take-off and landing of a multi-runway airport based on a hybrid genetic algorithm. The collaborative optimization method comprises the steps of 1) describing the composition of a flight queue; 2) setting the flight priority; 3) setting a priority coefficient of the flight on a single runway; 4) building a collaborative optimization model for an arrival and departure ground holding problem of the multi-runway airport; 5) setting a collaborative optimization evaluation criterion; 6) proposing a heuristic local search strategy; and 7) designing a hybrid genetic algorithm. The invention aims to solve a problem of applications of a ground holding strategy in the arrival and departure ground holding problem of the multi-runway airport and enable the delay cost to be reasonably allocated among arrival and departure flight queues. Compared with the prior art, the model built according to the invention takes reduction for the delay loss as an objective and realizes collaborative optimization for the delay loss; and the local search is guided to be performed towards a given direction by using the average delay loss of equivalent flights as heuristic information, so that the blindness of search is avoided, and collaboration optimization for the delay cost is significantly improved.

Description

technical field [0001] The invention relates to an optimization method for reducing flight delay costs, in particular to a multi-runway airport flight take-off and landing collaborative optimization method based on a hybrid genetic algorithm. Background technique [0002] With the rapid development of my country's economy, the demand for air transportation continues to rise, which has brought about the rise and rapid development of my country's air transportation industry. In 2014, various indicators of my country's airport throughput reached record highs, among which the passenger throughput was 391.95 million passengers, an increase of 10.7% over 2013, and only domestic routes completed 360.4 million passengers, of which Beijing, Shanghai and Guangzhou The passenger throughput of the airports in the three major cities accounted for 28.3% of the total airport passenger throughput. Due to the surge of air traffic flow, my country's existing air transport equipment and manage...

AI Technical Summary

Problems solved by technology

[0012] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a multi-runway airport flight take-off and landing collaborative optimization method based on hybrid genetic algorithm to solve the unreasonable distribution of flight mixed runways and the load of dedicated runways in the prior art. There are technical problems such as poor adjustment of flight volume and unreasonable allocation of delay losses between incoming and outgoing flights;

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