Applications of train routing selection methods for real-time railway traffic management

M. Samà, A. D’Ariano, D. Pacciarelli, P. Pellegrini, Joaquin Rodriguez
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引用次数: 1

Abstract

The real-time railway traffic management problem (rtRTMP) aims to solve time-overlapping conflicting track requests due to traffic disturbances. The size of the problem and the time required to solve it are affected by the number of routing alternatives available to each train. The real-time train routing selection problem (rtTRSP) chooses a feasible routing subset for each train to use as input for the rtRTMP. Recently, a computational analysis has been performed via Ant Colony Optimization and the RECIFE-MILP solver. This paper generalizes such analysis by considering a different rtRTMP model, objective function and solution approach. We adopt the AGLIBRARY solver, which is based an alternative graph model of the problem and minimizes the maximum consecutive delay. The aim is to develop real-time disturbance response strategies and to quantify the advantages of the selection of a subset of routings when using different solvers. We analyze how changes in the rtRTMP model are reflected in the rtTRSP and which modifications are required. The computational analysis is performed on two French infrastructures: the line around the city of Rouen and the Lille terminal station area. The analysis shows that solving the rtTRSP helps both solvers significantly, even if they are based on different models, objectives and algorithms.
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列车路线选择方法在铁路交通实时管理中的应用
实时轨道交通管理问题(rtRTMP)旨在解决由于交通干扰而导致的时间重叠的冲突轨道请求。问题的大小和解决问题所需的时间受每列火车可用的备选路线数量的影响。实时列车路线选择问题(rtrsp)为每列列车选择一个可行的路线子集作为rtRTMP的输入。最近,通过蚁群优化和RECIFE-MILP求解器进行了计算分析。本文通过考虑不同的rtRTMP模型、目标函数和求解方法,对上述分析进行了推广。我们采用AGLIBRARY求解器,它基于问题的备选图模型,最小化了最大连续延迟。目的是开发实时干扰响应策略,并量化在使用不同求解器时选择路由子集的优势。我们分析rtRTMP模型中的更改如何反映在rtrsp中,以及需要进行哪些修改。对两个法国基础设施进行了计算分析:鲁昂市周围的线路和里尔终点站区域。分析表明,即使基于不同的模型、目标和算法,求解rtrsp对两个求解器都有显著的帮助。
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