A Mixed Integer Linear Program for Optimizing the Utilization of Locomotives with Maintenance Constraints

Sarah Frisch (), Philipp Hungerländer (), Anna Jellen () and Dominic Weinberger ()
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Sarah Frisch: Alpen-Adria-Universität Klagenfurt
Philipp Hungerländer: Alpen-Adria-Universität Klagenfurt
Anna Jellen: Alpen-Adria-Universität Klagenfurt
Dominic Weinberger: Alpen-Adria-Universität Klagenfurt

A chapter in Operations Research Proceedings 2018, 2019, pp 103-109 from Springer

Abstract: Abstract In this paper we investigate the Locomotive Scheduling Problem, i.e., the optimization of locomotive utilization with prior known transports that must be performed. Railway timetables are typically planned a year in advance and then revised, updated and fixed for shorter time periods, e.g., for a week, during the year. Our aim is to assign locomotives to the trains such that the locomotive utilization is maximized considering maintenances. We model this optimization problem on a sparse weighted directed multigraph that defines the input variables for our proposed Mixed Integer Linear Program (MILP). We consider two different objective functions: We minimize over the number of deadhead kilometers, i.e., kilometers from a locomotive driven without pulling a train, and over the number of locomotives used. Finally, we conduct a computational study to compare the performance of our MILP with the different proposed objective functions and show how the MILP can be used within a rolling horizon approach.

Keywords: Locomotive scheduling problem; Maintenance constraints; Mixed integer linear programming (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-18500-8_14

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DOI: 10.1007/978-3-030-18500-8_14

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