客运专线动车组运用优化研究
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摘要
动车组作为客运专线承担客运量的一大主要载体,其在客运专线建设总投资中占较大的比重,如何在完成给定运输任务的前提下,通过合理的运输组织手段使动车组得到优化运用,减少其需要数量,合理安排动车组检修,从而减少动车组的投资,成为国内外专家、学者共同关注的热点问题。本文旨在从动车组列车优化接续的角度来研究客运专线动车组的优化运用及合理检修问题。本文所做的主要工作如下：
1、在查阅大量国内外研究成果的基础上,归纳总结了既有研究的有利之处,分析了其存在的局限性,指出当前动车组运用优化研究的意义。
2、运用归纳总结与系统分析的方法,分析总结了动车组运用优化的影响因素及其影响规律。明确了动车组运用优化的核心是使得满足列车运行图要求的动车组运用数量最小并实现动车组的均衡使用。
3、结合动车组运用理论与方法和数学规划理论与方法,在界定动车组运用的优化条件、基本参数的基础上,分别建立固定运用方式下、不固定运用方式下以及允许空车调拨情况下的动车组运用优化数学模型。
4、运用网络化理论方法,将不固定运用方式下的动车组运用优化数学模型转化为与TSP网络相类似的动车组运用优化网络模型；结合现代优化算法,提出了动车组运用优化网络模型的禁忌-蚂蚁搜索算法求解,给出了求解过程及流程。
5、以武广客运专线为算例,运用Matlab软件编程方法,编写Matlab程序对武广客运专线动车组运用优化网络模型进行求解,得到优化结果,验证动车组运用优化模型及其求解算法的科学性和可行性；运用对比分析法,将计算机优化结果与武广客运专线动车组运用实际情况进行对比分析。
6、归纳总结本文的主要研究工作与成果,得出本文的研究结论：本文所建立的模型及提出的算法是科学可行的,结合计算机得出的动车组运用优化结果比人工优化方法得出的结果更优,减少了昼间检修次数,也更有利于减少动车组需要数量,降低其投资。
As one of the main conveyances of passengers on PDL (Passenger Dedicated Lines), the EMU(Electricity Multiple Unit) takes up a significant proportion of the total investment in the construction of PDL, so, a series of studies on the issue of EMU operation have been conducted, such as how to reduce the EMU's investment through optimizing the using and maintenance of it by reasonable transportation organization thus reducing the number required to finish the given tasks. This paper aims to research issue of the optimized use and reasonable maintenance of the EMU on PDL from the point of view of the optimized connection of trains which includes:
1. Based on abundant domestic and foreign research achievements, this article summarized the benefits of existing researches, analyzed the limitations, and pointed out the significance of further research.
2. Using the mothod of summarizes and system analysis, this paper analyzed the influence factors and laws of the optimization of EMU operation. It maked clear the core is to minimize the number of EMUs that can realize train schedules and balancing the utilization of them.
3. Combining the theory and method of EMU operation and mathematical programming, based on the definition of optimization conditions and basic parameters of EMU operation, this paper respectively established the mathematical model under the different mode of EMU operation.
4. Using the method of network theory, this paper changed the mathematical model under the uncertain region operation mode into a network model which is similar to TSP network. Combined with the modern optimization algorithm, it put forward the use of tabu search ant algorithm to solve the model, and gave the solve process and procedure.
5. The feasibility of the model and the algorithm is proved by the case of Wu-Guang high-speed railway line by Matlab program experiments, and the results is compared with actual condition through comparative analyzing.
6. Summarized the main research work and achievement of this paper, and draw the conclusion:the model and algorithm were scientific and feasible, the results get by computer were better than actual, reduced the number of daytime maintenance, and more favourable for reducing the required number of EMU and its investment.
1、在查阅大量国内外研究成果的基础上,归纳总结了既有研究的有利之处,分析了其存在的局限性,指出当前动车组运用优化研究的意义。
2、运用归纳总结与系统分析的方法,分析总结了动车组运用优化的影响因素及其影响规律。明确了动车组运用优化的核心是使得满足列车运行图要求的动车组运用数量最小并实现动车组的均衡使用。
3、结合动车组运用理论与方法和数学规划理论与方法,在界定动车组运用的优化条件、基本参数的基础上,分别建立固定运用方式下、不固定运用方式下以及允许空车调拨情况下的动车组运用优化数学模型。
4、运用网络化理论方法,将不固定运用方式下的动车组运用优化数学模型转化为与TSP网络相类似的动车组运用优化网络模型；结合现代优化算法,提出了动车组运用优化网络模型的禁忌-蚂蚁搜索算法求解,给出了求解过程及流程。
5、以武广客运专线为算例,运用Matlab软件编程方法,编写Matlab程序对武广客运专线动车组运用优化网络模型进行求解,得到优化结果,验证动车组运用优化模型及其求解算法的科学性和可行性；运用对比分析法,将计算机优化结果与武广客运专线动车组运用实际情况进行对比分析。
6、归纳总结本文的主要研究工作与成果,得出本文的研究结论：本文所建立的模型及提出的算法是科学可行的,结合计算机得出的动车组运用优化结果比人工优化方法得出的结果更优,减少了昼间检修次数,也更有利于减少动车组需要数量,降低其投资。
As one of the main conveyances of passengers on PDL (Passenger Dedicated Lines), the EMU(Electricity Multiple Unit) takes up a significant proportion of the total investment in the construction of PDL, so, a series of studies on the issue of EMU operation have been conducted, such as how to reduce the EMU's investment through optimizing the using and maintenance of it by reasonable transportation organization thus reducing the number required to finish the given tasks. This paper aims to research issue of the optimized use and reasonable maintenance of the EMU on PDL from the point of view of the optimized connection of trains which includes:
1. Based on abundant domestic and foreign research achievements, this article summarized the benefits of existing researches, analyzed the limitations, and pointed out the significance of further research.
2. Using the mothod of summarizes and system analysis, this paper analyzed the influence factors and laws of the optimization of EMU operation. It maked clear the core is to minimize the number of EMUs that can realize train schedules and balancing the utilization of them.
3. Combining the theory and method of EMU operation and mathematical programming, based on the definition of optimization conditions and basic parameters of EMU operation, this paper respectively established the mathematical model under the different mode of EMU operation.
4. Using the method of network theory, this paper changed the mathematical model under the uncertain region operation mode into a network model which is similar to TSP network. Combined with the modern optimization algorithm, it put forward the use of tabu search ant algorithm to solve the model, and gave the solve process and procedure.
5. The feasibility of the model and the algorithm is proved by the case of Wu-Guang high-speed railway line by Matlab program experiments, and the results is compared with actual condition through comparative analyzing.
6. Summarized the main research work and achievement of this paper, and draw the conclusion:the model and algorithm were scientific and feasible, the results get by computer were better than actual, reduced the number of daytime maintenance, and more favourable for reducing the required number of EMU and its investment.
引文
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[7]符卓.优化车底使用数的客车运行方案图编制方法[J].铁道学报,1996,18(6)：69-74.
[8]Cynthia Barnhart,Natashia L.Boland.Flight String Models for Aircraft Fleeting and Routing [J]. Transportation Science,1998,32(3):208-220.
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[10]Feo T A, Bard J F. Flight Scheduling and Maintenance Base Planning [J]. Management Science,1989,35(12):1514-1532.
[11]Copalan R, Talluri K T. Aircraft Maintenance Routing Problem [J]. Operations Research, 1998,46(2):260-271.
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[16]赵鹏.高速铁路动车组和乘务员运用问题的研究[D].北京：北方交通大学,1998.
[17]耿敬春,肖荣国,倪少权,等.客运专线动车组周期性运用计划编制的研究[J].铁道学报,2006,28(4)：17-21.
[18]Sung Pil Hong, Kyung Min Kim,Kyungsik Lee,et al.A Pragmatic Algorithm for the Train-Set Routing:The Case of Korea High-Speed Railway[J]. mega, 2009,37(3): 637-645.
[19]花伟,张才春,徐利民,等.动车组簇式运用方式研究[J].铁道运输与经济,2010, 32(8)：76-80.
[20]赵鹏,胡安洲,杨浩.高速铁路动车组不固定区段使用条件下周转优化问题的研究[J].北方交通大学学报,1997,(12)：124-130.
[21]聂磊,赵鹏,杨浩,等.高速铁路动车组运用的研究[J].铁道学报,2001,23(3)：1-7.
[22]XIE Meiquan, MAO Baohua. Modeling Circulation of Train-Set with Multiple Routing [A]. Journal of Transportation Systems Engineering & Information Technology,2010, 10(3):50-57.
[23]Peeters M, Kroon L, et al. Circulation of railway rolling stock:a branch-and-price approach[J]. Computers & Operational Research,2008, 35 (2):538-556.
[24]Alfieri A, Rutger G, Kroon L, et al. Efficient circulation of railway rolling stock[J]. Transportation Science,2006,40 (3):378-391.
[25]Maróti G, Kroon L.Maintenance routing for train units:the transition model[J]. Transportation Science,2005,39(4):518-525.
[26]Maróti G, Kroon L. Maintenance routing for train units:the interchange model [J]. Computers & Operational Research, 2007,34 (4):1121-1140.
[27]杨军,杨浩,卢海波.遗传算法在动车组周转优化模型中的应用[J].铁道运输与经济,2004,26(7)：65-67.
[28]Bunte S, Kliewer N. An Overview on Vehicle Scheduling Models[R]. DSOR Working Papers:University of Paderborn, 2006.
[29]张杰,陈韬,施福根.客运专线动车组运用计划的计算机编制[J].西南交通大学学报,2006,41(5)：635-640.
[30]陈华群,唐协.应用神经网络优化高速铁路动车组周转的研究[J].中国安全生产科学技术,2006,2(2)：46-49.
[31]佟磊,聂磊,赵鹏.蚁群算法在动车组运用问题中的应用[J].交通运输系统工程与信息,2009,9(6)：161-167.
[32]蒋继磊,杨志杰.动车组运用计划编制及其优化[J].铁道运输与经济,2010,32(4)：37-48.
[33]赵鹏,富井规雄.动车组运用计划及其编制算法[J].铁道学报,2003,25(3)：1-7.
[34]赵鹏,富井规雄.基于概率局域搜索的动车组平日运用计划编制算法[J].系统工程理论与实践,2004,(2)：123-129.
[35]赵鹏,富井规雄.基于路段交换的多基地动车组运用计划的编制算法[J].铁道学报,2004,16(1)：7-11.
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