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A dynamic approach to vehicle scheduling

Author

Listed:
  • Huisman, D.
  • Freling, R.
  • Wagelmans, A.P.M.

Abstract

This paper presents a dynamic approach to the vehicle scheduling problem. We discuss the potential benefit of our approach compared to the traditional one, where the vehicle scheduling problem is solved only once for a whole period and the travel times are assumed to be fixed. In our dynamic approach, we solve a sequence of optimization problems, where we take into account different scenarios for future travel times. Because in the multiple-depot case we cannot solve the problem exactly within reasonable computation time, we use a "cluster-reschedule" heuristic where we first assign trips to depots by solving the static problem and then solve dynamic single-depot problems. We use new mathematical formulations of these problems that allow a fast solution by standard optimization software. We report on the results of a computational study with real life data, in which we compare different variants of our approach and perform a sensitivity analysis with respect to deviations of the actual travel times from the estimated ones.

Suggested Citation

  • Huisman, D. & Freling, R. & Wagelmans, A.P.M., 2001. "A dynamic approach to vehicle scheduling," ERIM Report Series Research in Management ERS-2001-35-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.
    • Handle: RePEc:ems:eureri:101
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    Citations

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    Cited by:

    1. Huisman, Dennis & Wagelmans, Albert P.M., 2006. "A solution approach for dynamic vehicle and crew scheduling," European Journal of Operational Research, Elsevier, vol. 172(2), pages 453-471, July.
    2. de Groot, S.W. & Huisman, D., 2004. "Vehicle and crew scheduling: solving large real-world instances with an integrated approach," Econometric Institute Research Papers EI 2004-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Keywords

    dynamic scheduling; public transport; stochastic programming; stochastic traveltimes; vehicle scheduling;
    All these keywords.

    JEL classification:

    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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