节点文献

基于微粒群算法的客运专线行车调度优化技术研究

The Technology Research of the Passenger Dedicated Line Dispatching Optimization Based on the Particle Swarm Algorithm

【作者】 都国报

【导师】 吕红霞;

【作者基本信息】 西南交通大学 , 交通运输规划与管理, 2010, 硕士

【摘要】 根据《我国铁路中长期建设规划》到2020年,我国主要铁路繁忙干线将实现“客货分离”的建设目标,本文将重点讨论客运专线范围内只运行旅客列车的行车组织模型优化问题。文章从客运专线运营调度机构设置入手,逐步讨论了客运专线运营调度业务流程,重点选取列车运行调整和列车进路控制两个方面的内容,详细介绍了有关问题的影响因素和问题的求解思路,为后面章节有关数学模型的建立打下理论铺垫。本文第四章结合列车调度员的日常工作内容——列车运行计划调整,本文重点介绍了列车运行调整的数学优化模型,并尝试运用微粒群算法求解这一复杂问题。考虑到客运专线实行集中调度,远程控制列车进路的需求特性,本文第五章还建立了车站到发线合理分配数学模型,并给出了运用离散型微粒群算法的求解过程,以及过程中几个关键问题的解决方案。主要内容如下:1.在介绍客运专线运营调度机构设置的基础上,从基本计划、实施计划和调整计划三个层次,对客运专线运营调度业务进行详细分析;2.选取行车调度指挥工作中,列车运行调整和列车进路控制两个重点内容进行研究,阐述了列车运行调整和车站到发线安排的相关影响因素,为该问题的数学建模提供理论基础;3.综合考虑列车运行调整中多个影响因素,以减少列车晚点时间总和与晚点列车数量为目标,建立数学优化模型,并尝试运用微粒群算法相关原理对该问题进行求解。较为清晰的阐述了算法求解的设计过程、计算步骤和一般方法,对过程中的多个关键问题进行研究,为该问题的进一步研究提供借鉴。4.以减少车站作业干扰、方便旅客、均衡合理运用到发线三个优化目标建立车站到发线合理运用的数学模型,并结合到发线变量的离散型取值特点,创新性运用二进制离散型微粒群算法进行求解,给出了算法的设计过程、计算方法以及算例分析,为今后该问题的深入研究提供参考。上述研究内容不仅可以帮助理解行车调度人员的工作内容和工作方法,对进一步提高我国铁路行车组织的科学性与合理性也有一定的帮助。

【Abstract】 The main railway lines of our country will implement "the new railway line only for passenger traffic and the existing railway line for commodity traffic", according to the long-term planning of China railway construction by 2020. This paper will focus on the traffic organization model optimization of transport organization only when passenger trains can be found on Passenger Dedicated Line.At the beginning, the operation scheduling setups of Passenger Dedicated Line is introduced, and then, the transport business of operation scheduling will be analyzed from the basic plan, implementation plan and operation plan, for three levels. And more attentions will be paid on the adjustment of train traveling and its route, which is the theory of the relevant mathematical model in the later chapter.What’s more, combining the adjustment of the train operation, which is the daily work contents of dispatchers, we will pay more attentions to the mathematical model of the train operation adjustment in the fourth chapter, which is solved by the particle swarm algorithm. In addition, considering the characteristics of centralized dispatching, the paper will also discuss the mathematical model of departure line distribution in the fifth chapter, the steps and some key points of the solving process by discrete particle swarm algorithm.The main content as follows:1. First, the operation scheduling setups of Passenger Dedicated Line is introduced,And then, the transport business of operation scheduling will be analyzed from the basic plan, implementation plan and operation plan, for three levels;2. Select the dispatching command work and the adjustment of train operation, the key points of the train operation scheduling. considering the related factors, we provide the theoretical foundation for the mathematical modeling;3. Considering the various limit of the train operation adjustment, we establish the mathematical model of the train operation automatically adjust, in order to reduce the total time delays and the number of behind schedule, and try to put the end to the complex optimization problem by using Particle Swarm Algorithm. At the same time, we will talk about the design process, which includes the calculate method, the steps and so on, further more, the multiple key points will be analyzed in detail in the end; 4. Considering the operation interference of railway station, the convenience for passengers and use the departure line balanced, we will establish the mathematical model of the reasonable use the railway station departure lines, and then, try to solve the problem by using the Binary Discrete Particle Swarm Algorithm combine with the feature of variables, what’s more, the design process, the calculation method and the example analysis will be given at end of the paper, providing the reference for further research.The research content can not only help understand dispatchers’ job content, but also do a good favor to improve the level of dispatching automation and decision-making intelligent.

节点文献中: 

本文链接的文献网络图示:

本文的引文网络