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Railway crew capacity planning problem with connectivity of schedules

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  • Suyabatmaz, Ali Çetin
  • Şahin, Güvenç

Abstract

We study a tactical level crew capacity planning problem in railways which determines the minimum required crew size in a region while both feasibility and connectivity of schedules are maintained. We present alternative mathematical formulations which depend on network representations of the problem. A path-based formulation in the form of a set-covering problem along with a column-and-row generation algorithm is proposed. An arc-based formulation of the problem is solved with a commercial linear programming solver. The computational study illustrates the effect of schedule connectivity on crew capacity decisions and shows that arc-based formulation is a viable approach.

Suggested Citation

  • Suyabatmaz, Ali Çetin & Şahin, Güvenç, 2015. "Railway crew capacity planning problem with connectivity of schedules," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 88-100.
  • Handle: RePEc:eee:transe:v:84:y:2015:i:c:p:88-100
    DOI: 10.1016/j.tre.2015.10.003
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    References listed on IDEAS

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    1. Diethard Klatte & Hans-Jakob Lüthi & Karl Schmedders (ed.), 2012. "Operations Research Proceedings 2011," Operations Research Proceedings, Springer, edition 127, number 978-3-642-29210-1, March.
    2. Silke Jütte & Marc Albers & Ulrich W. Thonemann & Knut Haase, 2011. "Optimizing Railway Crew Scheduling at DB Schenker," Interfaces, INFORMS, vol. 41(2), pages 109-122, April.
    3. A.T. Ernst & H. Jiang & M. Krishnamoorthy & H. Nott & D. Sier, 2001. "An Integrated Optimization Model for Train Crew Management," Annals of Operations Research, Springer, vol. 108(1), pages 211-224, November.
    4. Jütte, Silke & Thonemann, Ulrich W., 2012. "Divide-and-price: A decomposition algorithm for solving large railway crew scheduling problems," European Journal of Operational Research, Elsevier, vol. 219(2), pages 214-223.
    5. Erwin Abbink & Matteo Fischetti & Leo Kroon & Gerrit Timmer & Michiel Vromans, 2005. "Reinventing Crew Scheduling at Netherlands Railways," Interfaces, INFORMS, vol. 35(5), pages 393-401, October.
    6. A. Ç. Suyabatmaz & G. Şahin, 2012. "A Column-and-Row Generation Algorithm for a Crew Planning Problem in Railways," Operations Research Proceedings, in: Diethard Klatte & Hans-Jakob Lüthi & Karl Schmedders (ed.), Operations Research Proceedings 2011, edition 127, pages 335-340, Springer.
    7. Şahin, Güvenç & Yüceoğlu, Birol, 2011. "Tactical crew planning in railways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1221-1243.
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    Cited by:

    1. Kirsten Hoffmann & Udo Buscher & Janis Sebastian Neufeld & Felix Tamke, 2017. "Solving Practical Railway Crew Scheduling Problems with Attendance Rates," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(3), pages 147-159, June.
    2. Wang, Danni & Xiao, Fan & Zhou, Lei & Liang, Zhe, 2020. "Two-dimensional skiving and cutting stock problem with setup cost based on column-and-row generation," European Journal of Operational Research, Elsevier, vol. 286(2), pages 547-563.
    3. Neufeld, Janis S. & Scheffler, Martin & Tamke, Felix & Hoffmann, Kirsten & Buscher, Udo, 2021. "An efficient column generation approach for practical railway crew scheduling with attendance rates," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1113-1130.
    4. Pan, Hanchuan & Liu, Zhigang & Yang, Lixing & Liang, Zhe & Wu, Qiang & Li, Sijie, 2021. "A column generation-based approach for integrated vehicle and crew scheduling on a single metro line with the fully automatic operation system by partial supervision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    5. Heil, Julia & Hoffmann, Kirsten & Buscher, Udo, 2020. "Railway crew scheduling: Models, methods and applications," European Journal of Operational Research, Elsevier, vol. 283(2), pages 405-425.

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