区域多机场航班恢复的智能邻域算法研究
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摘要
为了充分利用实际运行中航班恢复方法,提高区域多机场不正常航班的恢复效率,综合考虑了机场、空管和航空公司在区域多机场系统中的运行能力限制,以降低总延误时间和恢复方案的执行总成本为优化目标,构建了区域多机场不正常航班恢复模型。然后将实际运行中航班恢复方法应用于算法新解产生机制,设计了基于智能邻域选择的多目标优化算法。仿真计算结果表明,与传统航班次序的调换方法相比,多种航班恢复方法的灵活运用有效减少了航班延误时间和方案的执行总成本,提高了区域多机场系统资源利用率与航班正常率。
In order to make full use of the actual running flight recovery method to improve the recovery efficiency of regional multi-airport irregular flights,this paper comprehensively considers the operational capacity limitations of airports,air traffic control and airlines in regional multi-airport systems,and reduces the total delay time and total cost of implementation of the recovery plan as the optimization goal,so a regional multi-airport irregular flight recovery model is established.Then,by applying the actual running flight recovery method to the algorithm new generation mechanism,a multi-objective optimization algorithm based on intelligent neighborhood selection is designed.The simulation results show that compared with the traditional flight order exchange method,the flexible use of multiple flight recovery methods effectively reduces the flight delay time and the total cost of implementation,and improves resource utilization and flight normality for regional multi-airport systems.
In order to make full use of the actual running flight recovery method to improve the recovery efficiency of regional multi-airport irregular flights,this paper comprehensively considers the operational capacity limitations of airports,air traffic control and airlines in regional multi-airport systems,and reduces the total delay time and total cost of implementation of the recovery plan as the optimization goal,so a regional multi-airport irregular flight recovery model is established.Then,by applying the actual running flight recovery method to the algorithm new generation mechanism,a multi-objective optimization algorithm based on intelligent neighborhood selection is designed.The simulation results show that compared with the traditional flight order exchange method,the flexible use of multiple flight recovery methods effectively reduces the flight delay time and the total cost of implementation,and improves resource utilization and flight normality for regional multi-airport systems.
引文
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[2]Clarke J P,Ren L,Mcclain E,et al.Evaluating Concepts for Operations in Metroplex Terminal Area Airspace[J].Journal of Aircraft,2014,49(3):758-773.
[3]Wieland F,Krueger W,Peng W,et al.Implementing a Combined Arrival,Departure,and Surface Scheduler for a Metroplex[C].Dallas,TX:AIAA Aviation Technology,Integration and Operations Conference,2013.
[4]Sidiropoulos S,Han K,Majumdar A,et al.Robust Identification of Air Traffic Flow Patterns in Metroplex Terminal Areas under Demand Uncertainty[J].Transportation Research Part C Emerging Technologies,2017,75:212-227.
[5]王莉莉,张潇潇.多机场协同决策进离场航班排序模型及算法研究[J].飞行力学,2016,34(1):90-94.
[6]张军峰,葛腾腾,郑志祥.多机场终端区进离场航班协同排序研究[J].交通运输系统工程与信息,2017,17(2):197-204.
[7]马园园,胡明华,尹嘉男,等.多机场终端区进离场交通流协同排序方法[J].航空学报,2017,38(2):220-232.
[8]靳学梅,白红利.多机场协同放行航班排序算法研究[C].沈阳:中国航空学会青年科技论坛,2014.
[9]江斌,彭瑛,赵征.区域多机场离场航班正常率特性分析[J].航空计算技术,2018,48(2):79-82.
[10]宾云鹏,邵荃,姜柯,等.基于旅客满意度与公平性的机场航班计划恢复[J].科学技术与工程,2018,18(14):275-278.
[11]Molina J,Lopez-Sanchez AD,Hernandez-Diaz AG,et al.AMulti-start Algorithm with Intelligent Neighborhood Selection for solving Multi-objective Humanitarian Vehicle Routing Problems[J].Journal of Heuristics,2018,24(2):111-133.