Multi-objective Flight Schedule Optimization Based on Improved Evolutionary Algorithm

Abstract:
Flight schedule optimization is an effective method to balance airport capacity and flight demand in the strategic phase. Firstly, the influence of flight wave on flight delay in a single airport system was explored based on historical operation data. Secondly, the one-day flight schedule was divided into regular time, prime time, and peak time according to the flight waveform. Then, a multi-objective optimization model is established to minimize the flight delay and flight slot offsets, and an improved evolutionary algorithm based on cross evolution is designed to solve the problem. Then, the actual operation data of Urumqi airport are used as an example to verify. The proposed algorithm is compared with the traditional evolutionary algorithm and greedy algorithm. Finally, the air ground joint model is constructed by AirTop software for simulation verification. The experimental results show that the improved evolutionary algorithm has better optimization effect and can effectively reduce the delay on the basis of reducing the amount of flight adjustment as much as possible. The research can provide theoretical and technical support for the rational allocation of flight time resources.