考虑风向不确定性的航班时刻优化
Flight Schedule Optimization Considering Wind Direction Uncertainty
王莉莉 1郭微萌1
作者信息
- 1. 中国民航大学空中交通管理学院,天津 300300
- 折叠
摘要
针对风向的不确定会影响航班的飞行时间和到达走廊口的时刻,造成走廊口出现流量过饱和的现象,提出基准风向的概念,并统计整个航季不同月份的基准风向概率;其次依据基准风向概率,以误差平方和与轮廓系数为指标将所有月份聚类为三类;然后基于聚类结果建立考虑风向不确定性的走廊口流量风险模型,并设计了改进粒子群算法实现模型求解;最后以首都机场的航班时刻表为例进行验证.研究表明:上述模型可以在一定程度上缓解风向不确定导致的走廊口流量饱和问题,增强航班时刻表的鲁棒性.相比初始航班时刻表,不同基准风向时的走廊口流量方差分别降低 26％和 14％,超出走廊口容量的总航班量减少 45％.
Abstract
The uncertainty of wind direction will affect the flight time and the arrival time of flights at the corri-dor,causing the phenomenon of traffic oversaturation at the corridor.The concept of reference wind direction is pro-posed,and the probability of reference wind direction in different months of the entire flight season is calculated;Sec-ondly,based on the probability of the benchmark wind direction,cluster all months into three categories using the sum of squared errors and contour coefficients as indicators;Then,based on the clustering results,a corridor flow risk model considering wind direction uncertainty was established,and an improved particle swarm algorithm was designed to solve the model;Finally,the flight schedule of Capital International Airport is used as an example for verification.The research has shown that the above model can to some extent alleviate the problem of corridor flow saturation caused by wind direction uncertainty and enhance the robustness of flight schedules.Compared to the initial flight schedule,the variance of corridor flow at different reference wind directions decreased by 26％ and 14％,respectively,and the total flight volume exceeding the capacity of the departure corridor decreased by 45％ .
关键词
航空运输/不确定性/粒子群算法/走廊口/航班时刻优化Key words
Air transportation/Uncertainty/Particle swarm optimization algorithm/Corridor/Flight schedule opti-mization引用本文复制引用
基金项目
国家自然科学基金(U1633124)
中国民航大学研究生科研创新资助项目(2022YJS088)
出版年
2024
NETL
NSTL
万方数据