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[TBE17] Optimization and simulation for robust railway rolling-stock planning

Revue Internationale avec comité de lecture : Journal Journal of Rail Transport Planning & Management, pp. 18, 2017, (doi:10.1016/j.jrtpm.2017.02.001)

Mots clés: Integer Linear Programming, Robustness, Optimization, Railway management, Rolling-stock planning

Résumé: In this paper, we focus on the problem of robust rolling-stock planning for French passenger trains. First, we characterize robustness and define some indicators for the evaluation of rolling-stock rosters. We take a particular interest in homogenizing turning-times in a roster in order to absorb potential delays. Then, we propose a new approach to solve the problem of robust rolling-stock planning. The SNCF reference tool (PRESTO) calculates a solution to the rolling-stock planning problem. It consists of a multi-step approach to cover demand while minimizing operating costs, and to further add maintenance slots to the roster. We propose an integrated ILP model to add robustness to a roster while maintaining low operating costs compared to PRESTO. We have carried out tests on nine real French regional transport instances, and we use a simulation module to evaluate the results. We observe a significant improvement in robustness indicators while maintaining low operating costs and meeting maintenance requirements.

Collaboration: R&D - SNCF

BibTeX

@article {
TBE17,
title="{Optimization and simulation for robust railway rolling-stock planning}",
author="S. Tréfond and A. Billionnet and S. Elloumi and H. Djellab",
journal="Journal of Rail Transport Planning & Management",
year=2017,
pages="18",
doi="10.1016/j.jrtpm.2017.02.001",
}