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

机译:列车路径选择方法在铁路实时交通管理中的应用

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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.
机译:实时铁路交通管理问题(rtRTMP)旨在解决由于交通干扰而造成的时间重叠冲突轨道请求。问题的大小和解决问题所需的时间受到每列火车可用的替代路线数量的影响。实时列车路线选择问题(rtTRSP)为每个列车选择一个可行的路线子集,用作rtRTMP的输入。最近,已通过蚁群优化和RECIFE-MILP求解器进行了计算分析。本文通过考虑不同的rtRTMP模型,目标函数和解决方案方法对这种分析进行了概括。我们采用AGLIBRARY求解器,该求解器基于问题的替代图形模型,并最大程度地减少了最大连续延迟。目的是开发实时干扰响应策略,并量化使用不同求解器时选择路由子集的优势。我们分析rtTRSP中如何反映rtRTMP模型中的更改以及需要进行哪些修改。计算分析是在两个法国基础设施上进行的:鲁昂市周围的线路和里尔码头区。分析表明,求解rtTRSP可以极大地帮助两个求解器,即使它们基于不同的模型,目标和算法也是如此。

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