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Rescheduling models for railway traffic management in large-scale networks

机译:大型网络中铁路交通管理的重新调度模型

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In the last decades of railway operations research, microscopic models have been intensively studied to support traffic operators in managing their dispatching areas. However, those models result in long computation times for large and highly utilized networks. The problem of controlling country-wide traffic is still open since the coordination of local areas is hard to tackle in short time and there are multiple interdependencies between trains across the whole network. This work is dedicated to the development of new macroscopic models that are able to incorporate traffic management decisions. Objective of this paper is to investigate how different levels of detail and number of operational constraints may affect the applicability of models for network-wide rescheduling in terms of quality of solutions and computation time. We present four different macroscopic models and test them on the Dutch national timetable. The macroscopic models are compared with a state-of-the-art microscopic model. Trade-off between computation time and solution quality is discussed on various disturbed traffic conditions.
机译:在最近的铁路运营研究中,对微观模型进行了深入研究,以支持交通运营商管理其调度区域。但是,这些模型导致大型和高利用率网络的计算时间较长。由于难以在短时间内解决本地协调问题,并且整个网络中火车之间存在多种相互依存关系,因此控制全国范围内交通的问题仍然悬而未决。这项工作致力于开发能够纳入交通管理决策的新的宏观模型。本文的目的是研究解决方案的质量和计算时间,不同级别的细节和操作约束的数量如何影响模型在整个网络范围内进行重新调度的适用性。我们提出了四种不同的宏观模型,并在荷兰国家时间表上对其进行了测试。将宏观模型与最新的微观模型进行比较。在各种受干扰的交通状况下,讨论了计算时间与解决方案质量之间的权衡。

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