基于大系统分解协调的CDM下不正常航班恢复优化
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摘要
针对不正常航班恢复以及民航调度系统中空管、机场和航空公司之间复杂的协同调度问题,设计了一个基于大系统分解协调的不正常航班调度系统分解方法.首先简述了基于CDM的航班调度系统结构及原理,然后针对不正常航班恢复所涉及的各参与主体利益需求,建立分解级协调级多级递阶结构的不正常航班恢复优化调度模型,对分解后的各子系统模型采用遗传算法优化求解.最后通过东北空域内各主要机场航班调度的算例验证分析,结果表明采用方法能够减少航班延误时间,提高航空管理和服务质量,为具体工程应用提供决策支持.
For the situation of irregular flights recovery and the complex collaborative scheduling problem about air transport control, airlines and airports, the decomposition method of irregular flights based on large-scale system decomposition-coordination was designed. Firstly, the structure and principle of flights scheduling system based on collaborative decision making(CDM) were introduced briefly. And the irregular flights optimal scheduling model of multi-level hierarchical structure was established for the participants' interests and demands of irregular flights recovery. Moreover, genetic algorithm is adopted in the optimization course for each decomposed subsystem model. Finally, he experimental analysis based on main airports flight scheduling of northeast region show that flight delays can be decreased, the level of aviation management and service quality can be improved by using the proposed method, which can provide decision support for solving the specific engineering application.
For the situation of irregular flights recovery and the complex collaborative scheduling problem about air transport control, airlines and airports, the decomposition method of irregular flights based on large-scale system decomposition-coordination was designed. Firstly, the structure and principle of flights scheduling system based on collaborative decision making(CDM) were introduced briefly. And the irregular flights optimal scheduling model of multi-level hierarchical structure was established for the participants' interests and demands of irregular flights recovery. Moreover, genetic algorithm is adopted in the optimization course for each decomposed subsystem model. Finally, he experimental analysis based on main airports flight scheduling of northeast region show that flight delays can be decreased, the level of aviation management and service quality can be improved by using the proposed method, which can provide decision support for solving the specific engineering application.
引文
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[5]杨欢,庞明宝,吴维.基于动态环境的机场航班实时调度优化研究[J]·数学的实践与认识,2017,47(1):63-69.
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[15]R.C.Carlson,I.Papamichail,M.Papageorgiou.Optimal mainstream traffic flow control of large scale motorway networks[J].Transportation Research Part C:Emerging Technologies,2010,18(2):193-212.
[16]李健.结合部路网匝道系统结构分解与协同控制方法研究[D].北京:北京交通大学,2012.
[17]卢昱.基于大系统分解协调算法的机组群优化控制[D].北京:华北电力大学,2015.
[2]Newell G F.Airport Capacity and Delays[J].Transportation Science,1979,13(13):201-241.
[3]Teodorovi D,Guberini S.Optimal dispatching strategy on an airline network after a schedule perturbation[J].European Journal of Operational Research,1984,15(2):178-182.
[4]吴刚,严俊.不正常航班恢复的一种改进的列生成算法[J]·南京航空航天大学学报,2014,46(2):329-334.
[5]杨欢,庞明宝,吴维.基于动态环境的机场航班实时调度优化研究[J]·数学的实践与认识,2017,47(1):63-69.
[6]罗凤娥,任栋,张成伟.CDM机制下不正常航班恢复的多目标规划模型[J].航空计算技术,2015,45(6):23-27.
[7]蒋欣欣,周航.基于CDM系统的航班动态性调度研究[J].武汉理工大学学报(交通科学与工程版),2015,39(5):1058-1063.
[8]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.
[9]Jens O.Brunner.Rescheduling of flights during ground delay programs with consideration of passenger and crew connections[J].Transportation Research Part E:Logistics and Transportation Review,2014,72:236-252.
[10]Vossen T,Ball M.Optimization and mediated bartering models for ground delay programs[J].Naval Research Logistics,2006,53(1):75-90.
[11]陈世林,胡明华.一种新的基于贪婪法的CDM时隙分配最优化算法[J].系统工程理论与实践,2008,28(10):144-149.
[12]张洪海,胡明华.CDM GDP飞机着陆时隙多目标优化分配[J].系统管理学报,2009,18(3):302-308.
[13]王湛,吴术.动态时隙再分配的分布式协同进化模型研究[J].交通运输系统工程与信息,2013,13(2):118-123.
[14]严俊,唐小卫,吴桐水.自主取消航班的协同式时隙二次指派方法[J].哈尔滨工业大学学报,2013,45(3):107-111.
[15]R.C.Carlson,I.Papamichail,M.Papageorgiou.Optimal mainstream traffic flow control of large scale motorway networks[J].Transportation Research Part C:Emerging Technologies,2010,18(2):193-212.
[16]李健.结合部路网匝道系统结构分解与协同控制方法研究[D].北京:北京交通大学,2012.
[17]卢昱.基于大系统分解协调算法的机组群优化控制[D].北京:华北电力大学,2015.