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The Locomotive Assignment Problem with Distributed Power at the Canadian National Railway Company

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  • Camilo Ortiz-Astorquiza

    (Department of Mathematics, Pontificia Universidad Javeriana, Bogotá D.C., Colombia;)

  • Jean-François Cordeau

    (HEC Montréal, Montreal, Quebec H3T 2A7, Canada;)

  • Emma Frejinger

    (Department of Computer Science and Operational Research, Université de Montréal, Montreal, Quebec H3T 1J4, Canada)

Abstract

Some of the most important optimization problems faced by railway operators arise from the management of their locomotive fleet. In this paper, we study a general version of the locomotive assignment problem encountered at the tactical level by one of the largest railroads in North America: the Canadian National (CN) Railway Company. We present a modeling framework with two integer linear programming formulations and contribute to the state of the art by allowing decisions on each train’s operating mode (distributed power or not) over the whole (weekly) planning horizon without partitioning it winto smaller time windows. Given the difficulty in solving the problem, one of the formulations is enhanced through various refinements, such as constraint relaxations, preprocessing, and fixed cost approximations. We thus achieve a significant reduction in the required computational time to solve instances of realistic size. We also present two versions of a Benders decomposition–based algorithm to obtain feasible solutions. On average, it allows a reduction of the associated computational time by two hours. Results from an extensive computational study and a case study with data provided by CN confirm the potential benefits of the model and solution approach.

Suggested Citation

  • Camilo Ortiz-Astorquiza & Jean-François Cordeau & Emma Frejinger, 2021. "The Locomotive Assignment Problem with Distributed Power at the Canadian National Railway Company," Transportation Science, INFORMS, vol. 55(2), pages 510-531, March.
    • Handle: RePEc:inm:ortrsc:v:55:y:2021:i:2:p:510-531
    DOI: 10.1287/trsc.2020.1030
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    References listed on IDEAS

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