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为有效缓解大流量、高密度机场日益严重的交通拥堵和航班延误现状,研究了多跑道离场航班优化调度问题。首先,从生产调度领域视角,将多跑道离场调度问题抽象为典型的车间作业调度NP-Hard组合优化问题;然后,面向航空运输各方利益需求,以航班延误、跑道容量和环境污染为优化目标,综合考虑航空器尾流影响、场面滑行和跑道穿越等各类限制因素,建立了独立离场模式下多跑道时空资源优化调度模型;最后,结合多目标优化及遗传算法基本理论,设计了带精英策略的非支配排序遗传算法(NSGA-II),寻求多跑道离场调度问题的Pareto最优解。仿真实验表明,模型可对独立离场航班进行优化配置,显著降低航班延误时间和航空发动机污染物排放量,并有效提升机场跑道容量。与随机和交替调度策略相比,优化调度策略执行效果显著,其中航班延误时间分别减少了51.2%和42.7%,所提方法可显著缓解大型繁忙机场离场航班起飞延误,有效提升航空运输服务品质。
In order to effectively alleviate the increasingly serious traffic congestion and flight delays in high-density and high-density airports, the problem of optimal flight scheduling for multi-runway departure flights is studied. First, from the perspective of production scheduling, the problem of multi-runway departure dispatching is abstracted as a typical NP-Hard combinatorial optimization problem. Then, for the interests of all parties involved in air transport, flight delay, runway capacity and environmental pollution are optimized Goal and comprehensively considering various wake factors such as aircraft wake influence, taxiway and runway traversal, the optimal scheduling model for multi-runway space-time resources under independent departure mode is established. Finally, combining with the multi-objective optimization and the basic theory of genetic algorithm, The elitist non-dominated ranking genetic algorithm (NSGA-II) seeks the Pareto optimal solution to the multi-runway departure dispatch problem. Simulation results show that the model can optimize the configuration of independent departure flights, significantly reduce the flight delay time and aircraft engine pollutant emissions, and effectively improve the airport runway capacity. Compared with the random and alternate scheduling strategies, the optimal scheduling strategy has achieved remarkable results, with flight delays reduced by 51.2% and 42.7% respectively. The proposed method can significantly alleviate the departure delay of departure flights from large-scale busy airports and effectively improve the quality of air transport services .