摘要
In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.
为适应协同决策需要,考虑进离场运行不同交通场景下空管、航司、机场和旅客的诉求差异,对进离场航班联合调度问题进行了系统的研究。根据容流匹配程度,判定进场/离场运行的交通状态为高峰或非高峰,分析不同交通状态下进场/离场运行各方诉求的差异,分别建立了各交通状态下进场/离场航班调度的数学模型;针对进场/离场运行交通状态组合所得的4种进离场联合运行交通场景,分别建立了相应的进离场航班联合调度双层规划模型并设计精英保留的遗传算法求解。结果表明:较先到先服务方法,在进场高峰/离场非高峰和进场高峰/离场高峰场景下,优化调度结果中离场航班均衡满意度得到提升,离场航班流的跑道占用时间减少了38.8%;在进场非高峰/离场非高峰和离场高峰/进场非高峰的场景下,优化调度结果中进场航班均衡延误时间大幅减少,离场航班均衡满意度提升了77.6%,离场航班流的跑道占用时间减少了46.6%。与其他4种策略相比,优化调度方法更好地权衡了公平与效率,调度结果更加合理可行。
基金
supported by Nanjing University of Aeronautics and Astronautics Graduate Innovation Base(Laboratory)Open Fund(No.kfjj20200717).
