摘要
随着交通量需求的增加,为了优化进场航班的运行效能和提升安全性,提出点融合系统(point merge system,PMS)的优先级模型,根据航班的重要程度(航程是否连续)、航班的载客率以及航班的类型可以确定航班的优先级,以最小化进场航班的总延误成本及排序边飞行总时间为目标函数,以排序边唯一,尾流间隔,进入点融合系统时间窗,排序边长度,位置转换次数为约束,并以广州白云机场进场程序为例,采用改进的非支配排序遗传算法(non-dominated sorting genetic algorithmⅡ,NSGA-Ⅱ)求得航班落地的最终序列。结果表明:改进的NSGA-Ⅱ算法与先到先服务和未改进的遗传算法进行对比,总延误成本分别降低了4.1%和1.9%,排序边飞行总时间分别降低了32.5%和21.6%。可见该模型算法能有效地降低延误成本,减少飞行时间,从而缓解机场空域压力,提高飞行效率。
As the demand for air traffic increases,in order to optimize the operational efficiency and enhance safety of arriving flights,a priority model for the point merge system(PMS)was proposed.The determination of each flight s priority was based on its importance,taking into account factors such as the continuity of the flight,passenger load,and flight type.The objective function aimed to minimize the total delay cost and the total sorting edge flying time of arriving flights.Constraints encompassed unique sorting edges,wake turbulence separation,entry time window for the point merge system,sorting edge length,and the number of position transitions.Guangzhou Baiyun Airport s arrival procedures were exemplified,and the final sequence of landing flights was obtained using an improved non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ).The results show that the improved NSGA-Ⅱalgorithm,compared to first-come-first-served and unimproved genetic algorithms,respectively decreased the total delay cost by 4.1%and 1.9%,and the total flight time by 32.5%and 21.6%.It is concluded that this model effectively reduces delay costs,decreases flying time,thereby alleviating airport airspace pressure,and enhancing flight efficiency.
作者
黄晋
邱瑶瑶
张磊
焦瑶瑶
HUANG Jin;QIU Yao-yao;ZHANG Lei;JIAO Yao-yao(School of Air Traffic Management,Civil Aviation Flight University of China,Guanghan 618307,China)
出处
《科学技术与工程》
北大核心
2024年第36期15708-15715,共8页
Science Technology and Engineering
基金
民航安全能力建设项目(FY2024MHBZ-12)。
