基于遗传算法的离场航班时刻优化

Optimization of Departure Flight Schedule Based on Genetic Algorithm

针对枢纽机场航班延误和放行正常率低的现象,对离场航班进行合理的调度,将航班延误降到最低,提高放行正常率。作者从机场运行角度出发,考虑了机场实际放行能力、航班调度难度和管制间隔、跑道容量等因素,建立了离场航班优化调度模型,引入遗传算法对该模型进行求解。并利用AirTop对优化结果仿真验证,以上海虹桥国际机场为例,利用所提算法对离港航班时刻进行优化,AirTop仿真结果表明,优化后的航班总延误时间减少了32.3%,延误航班数量也减少了28%。因此,上述算法可以有效地提高机场运行效率,减少航班延误,从而提高经济效益。

In view of the phenomenon of flight delay and low normal release rate at the hub airport, the departure flights shall be reasonably scheduled to minimize the flight delay and improve the normal release rate. From the perspective of airport operation, the author considered the factors such as actual airport release capacity, flight scheduling difficulty and control interval, runway capacity and other factors, and established an optimal scheduling model for departure flights, introducing genetic algorithms to solve the model. AirTop was used to simulate and verify the optimization results. Taking Shanghai Hongqiao International Airport as an example, the proposed algorithm was used to optimize the departure flight time. AirTop simulation results show that the total delay time of the optimized flight is reduced by 32.3%,and the number of delayed flights is also Reduced by 28%. Therefore, the algorithm can effectively improve airport operation efficiency, reduce flight delays, and thus improve economic efficiency.