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Two-phase heuristic for SNCF rolling stock problem

Author

Listed:
  • Mirsad Buljubašić

    (Ecole des Mines d’Alès)

  • Michel Vasquez

    (Ecole des Mines d’Alès)

  • Haris Gavranović

    (International University of Sarajevo)

Abstract

A two-phase approach was adopted to solve the problem given during the ROADEF/EURO Challenge 2014 competition. The problem focuses on rolling stock management at railway sites, as defined by French Railways (SNCF). In the first phase, a train assignment problem is solved by combining a greedy heuristic procedure with integer programming. The objective is to maximize the number of assigned departures while meeting technical constraints. The second phase consists of scheduling train movements inside the station while minimizing the number of cancelled (uncovered) arrivals and departures. This schedule has to comply with resource constraints such as capacity, length, order of trains, etc. A constructive heuristic is used to build a feasible schedule, which is subject to improvement by an iterative procedure based on a local search. Experiment results, that demonstrate the effectiveness of our approach on the large scale instances provided by SNCF, are presented hereafter.

Suggested Citation

  • Mirsad Buljubašić & Michel Vasquez & Haris Gavranović, 2018. "Two-phase heuristic for SNCF rolling stock problem," Annals of Operations Research, Springer, vol. 271(2), pages 1107-1129, December.
    • Handle: RePEc:spr:annopr:v:271:y:2018:i:2:d:10.1007_s10479-017-2550-z
    DOI: 10.1007/s10479-017-2550-z
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    References listed on IDEAS

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    1. Richard Freling & Ramon M. Lentink & Leo G. Kroon & Dennis Huisman, 2005. "Shunting of Passenger Train Units in a Railway Station," Transportation Science, INFORMS, vol. 39(2), pages 261-272, May.
    2. Dennis Huisman & Leo G. Kroon & Ramon M. Lentink & Michiel J. C. M. Vromans, 2005. "Operations Research in passenger railway transportation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 467-497, November.
    3. Corman, Francesco & D'Ariano, Andrea & Pacciarelli, Dario & Pranzo, Marco, 2010. "A tabu search algorithm for rerouting trains during rail operations," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 175-192, January.
    4. Freling, R. & Lentink, R.M. & Kroon, L.G. & Huisman, D., 2002. "Shunting of Passenger Train Units in a Railway Station," ERIM Report Series Research in Management ERS-2002-74-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Lentink, R.M. & Fioole, P-J. & Kroon, L.G. & van 't Woudt, C., 2003. "Applying Operations Research techniques to planning of train shunting," ERIM Report Series Research in Management ERS-2003-094-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    Cited by:

    1. Christian Artigues & Eric Bourreau & Vincent Jost & Safia Kedad-Sidhoum & François Ramond, 2018. "Trains do not vanish: the ROADEF/EURO challenge 2014," Annals of Operations Research, Springer, vol. 271(2), pages 1091-1105, December.
    2. Michel Vasquez & Mirsad Buljubasic & Saïd Hanafi, 2023. "An efficient scenario penalization matheuristic for a stochastic scheduling problem," Journal of Heuristics, Springer, vol. 29(2), pages 383-408, June.

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