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机场群共用航路点的航班排序模型及算法 被引量:4

Aircraft Sequencing Modeling and Algorithm for Shared Waypoints in Airport Group
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摘要 机场群上空空域资源共享、运行耦合复杂,拥堵往往发生在共用航路点。为缓解空域拥堵和航班延误问题,开展了机场群共用航路点的优化排序研究。针对共用航路点的运行特征,引入惩罚因子并以总延误时间成本最小为优化目标,建立了机场群共用航路点的航班优化排序模型,基于滑动时间窗算法和粒子群优化算法的原理提出了TW-PSO组合优化算法对模型进行求解。选取京津冀机场群过共用航路点的航班进行算例仿真,结果表明:TW-PSO组合优化算法与FCFS算法、滑动时间窗算法、粒子群优化算法相比在高峰时段的总延误时间成本分别减少了216,212,161 min;在算法性能方面,具有比经典算法迭代次数少、优化效果更佳的优点,能有效缓解航班延误问题,改善机场群的协同运行效率。 Congestion often occurs on shared waypoints due to shared airspace resources in airport group and compli⁃cated operation coupling.The work studies sequencing optimization of the shared waypoint in the airport group to alle⁃viate the problems of airspace congestion and flight delays.Aiming at the operating characteristics of a shared way⁃point,penalty factors are adopted to minimize the total delay time cost as the optimization goal,and a model is devel⁃oped to optimize aircraft sequencing on the shared waypoints in the airport group.Based on the principles of sliding time window algorithm and particle swarm optimization algorithm,a TW-PSO combined optimization algorithm is pro⁃posed to solve the model.The aircrafts of the Beijing-Tianjin-Hebei airport group passing the shared waypoints are se⁃lected for a simulation.The results show that the total delay time cost of the TW-PSO combined optimization algorithm in peak hours compared with the FCFS algorithm,sliding time window algorithm,and particle swarm optimization algo⁃rithm,reduced by 216,212,and 161 min,respectively.Therefore,in terms of algorithm performance,it has the advan⁃tages of fewer iterations and better optimization outcomes than classic algorithms,which can alleviate flight delays and improve the coordinated operation of the airport group.
作者 王莉莉 林雍雅 WANG Lili;LIN Yongya(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)
出处 《交通信息与安全》 CSCD 北大核心 2021年第5期93-99,136,共8页 Journal of Transport Information and Safety
基金 国家自然科学基金委员会与中国民用航空局联合资助项目(U1633124)资助。
关键词 航空运输 机场群 航班优化排序 滑动时间窗算法 粒子群优化算法 air transport airport group optimal aircraft sequencing sliding time window algorithm particle swarm op⁃timization algorithm
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