One of the many problems faced by rail transportation companies is to optimize the utilization of the available stock of locomotives and cars. In this paper, we describe a decomposition method for the simultaneous assignment of locomotives and cars in the context of passenger transportation. Given a list of train legs and a fleet composed of several types of equipment, the problem is to determine a set of minimum cost equipment cycles such that every leg is covered using appropriate equipment. Linking constraints, which appear when both locomotives and cars are treated simultaneously, lead to a large integer programming formulation. We propose an exact algorithm, based on the Benders decomposition approach, that exploits the separability of the problem. Computational experiments carried on a number of real-life instances indicate that the method finds optimal solutions within short computing times. It also outperforms other approaches based on Lagrangian relaxation or Dantzig-Wolfe decomposition, as well as a simplex-based branch-and-bound method.
CITATION STYLE
Cordeau, J. F., Soumis, F., & Desrosiers, J. (2000). Benders decomposition approach for the locomotive and car assignment problem. Transportation Science, 34(2), 133–149. https://doi.org/10.1287/trsc.34.2.133.12308
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