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Single-Car Routing in Rail Freight Transport

Author

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  • Armin Fügenschuh

    (Department of Mechanical Engineering, Helmut Schmidt University/University of the Federal Armed Forces Hamburg, 22043 Hamburg, Germany)

  • Henning Homfeld

    (Universität Erlangen-Nürnberg, Lehrstuhl für Wirtschaftsmathematik, 91058 Erlangen, Germany)

  • Hanno Schülldorf

    (Universität Erlangen-Nürnberg, Lehrstuhl für Wirtschaftsmathematik, 91058 Erlangen, Germany; and DB Mobility Logistics AG, Transportation Network Development and Transport Models (GSV), 60326 Frankfurt am Main, Germany)

Abstract

Single cars in rail freight service are bundled into trains at classification yards. On the way from their respective origins via intermediate yards to their destinations, they are reclassified several times, which is a time-consuming and personally consuming procedure. The single-car routing problem asks for the design of such routes for a given set of orders (origin-destination pairs with associated data) on an infrastructure network, such that the number of trains and their travel distances are minimal. A number of hard restrictions must be obeyed, such as restrictions for the train length and weight, and capacity restrictions for the yards, as well as further operational rules. We present a mixed-integer linear programming (MILP) formulation for this car-routing problem arising at Deutsche Bahn, one of the largest European railway companies. In a further step, we refine the handling of the turnover waiting time for the cars in the yards, which leads to the inclusion of nonlinear constraints in the model. Using adequate linearization techniques, this model can be reduced to a MILP again. Instances of this model turn out to be hard to solve. Further techniques are thus presented to speed up the numerical solution process, among them a tree-based reformulation and heuristic cuts. The different model formulations are computationally compared on a test set of randomly generated instances whose sizes are comparable to real-world instances. Using state-of-the-art MILP solvers, optimal or near-optimal solutions can be computed within a reasonable time frame.

Suggested Citation

  • Armin Fügenschuh & Henning Homfeld & Hanno Schülldorf, 2015. "Single-Car Routing in Rail Freight Transport," Transportation Science, INFORMS, vol. 49(1), pages 130-148, February.
  • Handle: RePEc:inm:ortrsc:v:49:y:2015:i:1:p:130-148
    DOI: 10.1287/trsc.2013.0486
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    References listed on IDEAS

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    Cited by:

    1. Ruf, Moritz & Cordeau, Jean-François, 2021. "Adaptive large neighborhood search for integrated planning in railroad classification yards," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 26-51.
    2. Ralf Borndörfer & Torsten Klug & Thomas Schlechte & Armin Fügenschuh & Thilo Schang & Hanno Schülldorf, 2016. "The Freight Train Routing Problem for Congested Railway Networks with Mixed Traffic," Transportation Science, INFORMS, vol. 50(2), pages 408-423, May.
    3. Chen, Chongshuang & Dollevoet, Twan & Zhao, Jun, 2018. "One-block train formation in large-scale railway networks: An exact model and a tree-based decomposition algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 1-30.
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    5. Wang, Dian & Zhao, Jun & Peng, Qiyuan, 2022. "Optimizing the loaded train combination problem at a heavy-haul marshalling station," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).

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