Multi-period railway line planning for integrated passenger-freight transportation

Wanru Chen, Rolf N. van Lieshout, Dezhi Zhang, Tom Van Woensel
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Abstract

This paper addresses a multi-period line planning problem in an integrated passenger-freight railway system, aiming to maximize profit while serving passengers and freight using a combination of dedicated passenger trains, dedicated freight trains, and mixed trains. To accommodate demand with different time sensitivities, we develop a period-extended change&go-network that tracks the paths taken by passengers and freight. The problem is formulated as a path-based mixed integer programming model, with the linear relaxation solved using column generation. Paths for passengers and freight are dynamically generated by solving pricing problems defined as elementary shortest-path problems with duration constraints. We propose two heuristic approaches: price-and-branch and a diving heuristic, with acceleration strategies, to find integer feasible solutions efficiently. Computational experiments on the Chinese high-speed railway network demonstrate that the diving heuristic outperforms the price-and-branch heuristic in both computational time and solution quality. Additionally, the experiments highlight the benefits of integrating freight, the advantages of multi-period line planning, and the impact of different demand patterns on line operations.
客货运输一体化的多期铁路线路规划
本文探讨了客货运一体化铁路系统中的多期线路规划问题,目的是在使用专用客运列车、专用货运列车和混合列车为客运和货运提供服务的同时实现利润最大化。为了满足不同时间敏感性的需求,我们开发了一个周期扩展的换乘和出发网络,跟踪客运和货运的路径。该问题被表述为一个基于路径的混合整数编程模型,并使用列生成法解决线性松弛问题。客运和货运的路径是通过求解定价问题动态生成的,定价问题定义为带有持续时间约束的基本最短路径问题。我们提出了两种启发式方法:价格-分支和潜水启发式,并采用加速策略,以高效地找到整数可行解。在中国高速铁路网上进行的计算实验表明,潜水启发式在计算时间和解的质量上都优于价格-分支启发式。此外,实验还强调了整合货运的好处、多期线路规划的优势以及不同需求模式对线路运营的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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