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Simultaneous Vehicle and Crew Scheduling in Urban Mass Transit Systems

Author

Listed:
  • Knut Haase

    (Institut für Betriebswirtschaftslehre, Universität Hohenheim, Stuttgart, Germany)

  • Guy Desaulniers

    (École Polytechnique and GERAD, 3000 chemin de la Côte-Ste-Catherine, Montréal, Québec, Canada, H3T 2A7)

  • Jacques Desrosiers

    (École des Hautes Études Commerciales and GERAD, 3000 chemin de la Côte-Ste-Catherine, Montréal Québec, Canada, H3T 2A7)

Abstract

This paper presents an exact approach for solving the simultaneous vehicle and crew scheduling problem in urban mass transit systems. We consider the single depot case with a homogeneous fleet of vehicles. This approach relies on a set partitioning formulation for the driver scheduling problem that incorporates side constraints for the bus itineraries. The proposed solution approach consists of a column generation process (only for the crew schedules) integrated into a branch-and-bound scheme. The side constraints on buses guarantee that an optimal vehicle assignment can be derived afterwards in polynomial time. A computational study shows that this approach out-performs the previous methods found in the literature for a set of randomly generated instances. A heuristic version of the solution approach is also proposed and tested on larger instances.

Suggested Citation

  • Knut Haase & Guy Desaulniers & Jacques Desrosiers, 2001. "Simultaneous Vehicle and Crew Scheduling in Urban Mass Transit Systems," Transportation Science, INFORMS, vol. 35(3), pages 286-303, August.
    • Handle: RePEc:inm:ortrsc:v:35:y:2001:i:3:p:286-303
    DOI: 10.1287/trsc.35.3.286.10153
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    References listed on IDEAS

    as
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    8. Michel Gamache & François Soumis & Gérald Marquis & Jacques Desrosiers, 1999. "A Column Generation Approach for Large-Scale Aircrew Rostering Problems," Operations Research, INFORMS, vol. 47(2), pages 247-263, April.
    9. A. Mingozzi & M. A. Boschetti & S. Ricciardelli & L. Bianco, 1999. "A Set Partitioning Approach to the Crew Scheduling Problem," Operations Research, INFORMS, vol. 47(6), pages 873-888, December.
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