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A multi-objective optimization-simulation approach for real time rescheduling in dense railway systems

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  • Altazin, Estelle
  • Dauzère-Pérès, Stéphane
  • Ramond, François
  • Tréfond, Sabine

Abstract

Rescheduling trains in dense railway systems to cope in real time with limited disturbances is a challenging problem with multiple conflicting objectives and various types of decisions. Based on the French railway system in the Paris region, this paper proposes an approach combining multi-objective optimization, to select rescheduling decisions, and macroscopic simulation, to compute the objectives associated to these decisions. Possible decisions include canceling or short-turning trains and skipping or adding stops. Three main objectives are optimized to propose multiple solutions to the decision makers: The recovery time, the quality of service for passengers and the number of decisions. Two greedy heuristics are presented whose results on actual data are compared with a full enumeration method. The multi-objective feature of the approach is also analyzed. The implementation and successful validation in real life of a decision-support tool, that is now implemented, is discussed.

Suggested Citation

  • Altazin, Estelle & Dauzère-Pérès, Stéphane & Ramond, François & Tréfond, Sabine, 2020. "A multi-objective optimization-simulation approach for real time rescheduling in dense railway systems," European Journal of Operational Research, Elsevier, vol. 286(2), pages 662-672.
  • Handle: RePEc:eee:ejores:v:286:y:2020:i:2:p:662-672
    DOI: 10.1016/j.ejor.2020.03.034
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    8. Zhang, Chuntian & Gao, Yuan & Cacchiani, Valentina & Yang, Lixing & Gao, Ziyou, 2023. "Train rescheduling for large-scale disruptions in a large-scale railway network," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).

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