Equivalences between analytical railway capacity methods

Qinglun Zhong , Chang’an Xu , Rudong Yang , Qingwei Zhong
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引用次数: 2

Abstract

Capacity analysis is of central importance in railway operation. Existing methods divide the infrastructure of question into smaller sections when computing the consumed capacity, which makes them nontransferable for real-world operation. We first review and enhance the UIC compression method, which results in a combination–reconstruction (ComRec) method to compute the compressed timetable graph of the whole infrastructure. Secondly, we propose a triangular-gap-problem-based (TGP) method to compute the headway times of train pairs when no more than one train lies within the separation gap of two trains. Then we show TGP method produces an compressed timetable graph equivalent to that by the ComRec method. Max-plus algebra approach determines the consumed capacity by solving an eigenvalue problem, and the solution corresponds to a timed event network as the compressed timetable. And by their correspondence, we show that these three methods are equivalent. Finally, we establish correspondences between the capacity methods and linear programming models. In this way, we were able to specify the condition when they give the same result and how infrastructure dividing underestimates capacity.

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分析铁路运力方法的等价性
运力分析在铁路运营中具有重要意义。现有的方法在计算消耗的容量时将有问题的基础设施划分为更小的部分,这使得它们对于现实世界的操作是不可转移的。我们首先回顾并改进了UIC压缩方法,该方法产生了一种组合重建(ComRec)方法来计算整个基础设施的压缩时间表图。其次,我们提出了一种基于三角形间隙问题(TGP)的方法来计算当不超过一列列车位于两列列车的间隔间隙内时列车对的间隔时间。然后我们证明了TGP方法产生的压缩时间表图与ComRec方法产生的时间表图等价。最大加代数方法通过求解特征值问题来确定消耗的容量,并且该解决方案对应于作为压缩时间表的定时事件网络。通过它们的对应关系,我们证明了这三种方法是等价的。最后,我们建立了容量方法和线性规划模型之间的对应关系。通过这种方式,我们能够指定它们给出相同结果的条件,以及基础设施划分如何低估容量。
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来源期刊
CiteScore
7.10
自引率
8.10%
发文量
41
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