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Communication Dans Un Congrès Année : 2021

An improved approach for train routing selection in large railway stations

Résumé

The real-time Railway Traffic Management Problem (rtRTMP) is the problem of detecting and solving time-overlapping conflicting requests done by multiple trains on the same track resources. This problem consists in retiming, reordering and rerouting trains in such a way that the propagation of disturbances in the railway network is minimized. The rtRTMP is an NP-complete problem and finding good strategies to simplify its solution process is paramount to obtain good quality results in a short computation time. Solving the Train Routing Selection Problem (TRSP) aims to reduce the size of rtRTMP instances by limiting the number of routing variables: during a pre-processing the most promising routing alternatives among the available ones are selected for each train. These alternatives are the only ones to be then used in the rtRTMP solution. A first version of the TRSP has been recently proposed in the literature. This paper presents an improved TRSP model for stations where rolling stock re-utilization timing constraints and estimation of train delay propagation are taken into account. Additionally, a parallel Ant Colony Optimization (ACO) algorithm is proposed. We analyze the impact of the TRSP model and algorithm on the rtRTMP through a thorough computational campaign performed on a French case study with timetable disturbances and infrastructure disruptions. The model presented leads to a better correlation between TRSP and rtRTMP solutions, and the proposed ACO algorithm outperforms the former state-of-the-art.
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Dates et versions

hal-03467243 , version 1 (06-12-2021)

Identifiants

  • HAL Id : hal-03467243 , version 1

Citer

Bianca Pascariu, Marcella Sama, Paola Pellegrini, Andrea D'ariano, Dario Pacciarelli, et al.. An improved approach for train routing selection in large railway stations. RailBeijing 2021, 9th International Conference on Railway Operations Modelling and Analysis (ICROMA), Nov 2021, Pékin, China. ⟨hal-03467243⟩
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