Transportation Research Part B: Methodological ( IF 6.8 ) Pub Date : 2020-04-25 , DOI: 10.1016/j.trb.2020.03.008 Christopher Szymula , Nikola Bešinović
The performance and behaviour of critical infrastructure in case of disruptions is an important topic and we are still lacking of insights. Due to disruptions, infrastructure becomes unavailable and may force the trains and passengers to adapt. In this paper, we introduce a problem of railway network vulnerability from the perspective of passenger flows and train operations. We propose a new Railway Network Vulnerability Model (RNVM) to assess the vulnerability of the system by finding the critical combination of links, which cause the most adverse consequences to passengers and trains. To solve this challenging problem, we present a RNVM framework, which combines two heuristics based on column and row generation with mixed integer linear programming, to efficiently model alternative passenger flows and infrastructure constraints. The developed framework provides the critical combination of links, the corresponding passenger flows, train routes and timetables. We demonstrate the performance of the RNVM framework on the real-world instance of a part of the Dutch railway network. The results show that the RNVM framework can efficiently reassign passenger flows and reroute trains during disruptions. The results also reveal that the critical links are highly demand dependent rather than a static feature of the networks topology. Finally, the computation times remain small when increasing the number of disrupted links as well as the size of the passenger demand, which allows fast and efficient network vulnerability assessment.
中文翻译:
铁路网络以乘客为中心的脆弱性评估
关键基础设施在发生故障时的性能和行为是一个重要主题,我们仍然缺乏见识。由于中断,基础设施变得不可用,并且可能迫使火车和乘客适应。本文从客流和列车运行的角度介绍了铁路网络的脆弱性问题。我们提出了一种新的铁路网络漏洞模型(RNVM),通过查找对乘客和火车造成最不利后果的关键链接组合来评估系统的漏洞。为了解决这个具有挑战性的问题,我们提出了一个RNVM框架,该框架将基于列和行生成的两种启发式方法与混合整数线性规划相结合,以有效地模拟替代性客流和基础设施约束。开发的框架提供了链接,相应的客流,火车路线和时间表的关键组合。我们将在荷兰铁路网络的一部分的真实世界实例上演示RNVM框架的性能。结果表明,RNVM框架可以在中断期间有效地重新分配旅客流量和路线。结果还表明,关键链路高度依赖需求,而不是网络拓扑的静态功能。最后,当增加中断链路的数量以及乘客需求的大小时,计算时间保持很小,从而可以快速有效地评估网络漏洞。我们将在荷兰铁路网络的一部分的真实世界实例上演示RNVM框架的性能。结果表明,RNVM框架可以在中断期间有效地重新分配旅客流量和火车路线。结果还表明,关键链路高度依赖需求,而不是网络拓扑的静态功能。最后,当增加中断链路的数量以及乘客需求的大小时,计算时间保持很小,从而可以快速有效地评估网络漏洞。我们将在荷兰铁路网络的一部分的真实世界实例上演示RNVM框架的性能。结果表明,RNVM框架可以在中断期间有效地重新分配旅客流量和路线。结果还表明,关键链路高度依赖需求,而不是网络拓扑的静态功能。最后,当增加中断链路的数量以及乘客需求的大小时,计算时间保持很小,从而可以快速有效地评估网络漏洞。结果还表明,关键链路高度依赖需求,而不是网络拓扑的静态功能。最后,当增加中断链路的数量以及乘客需求的大小时,计算时间保持很小,从而可以快速有效地评估网络漏洞。结果还表明,关键链路高度依赖需求,而不是网络拓扑的静态功能。最后,当增加中断链路的数量以及乘客需求的大小时,计算时间保持很小,从而可以快速有效地评估网络漏洞。