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Solving Practical Railway Crew Scheduling Problems with Attendance Rates

Author

Listed:
  • Kirsten Hoffmann

    (Lehrstuhl für BWL, insbes. Industrielles Management)

  • Udo Buscher

    (Lehrstuhl für BWL, insbes. Industrielles Management)

  • Janis Sebastian Neufeld

    (Lehrstuhl für BWL, insbes. Industrielles Management)

  • Felix Tamke

    (Lehrstuhl für BWL, insbes. Industrielles Management)

Abstract

Arising from a practical problem in German rail passenger transport, a prototype for a multi-period railway crew scheduling problem with attendance rates for conductors is developed and evaluated in this paper. The consideration of attendance rates is of increasing importance in regional transport networks and requires decision support. For this purpose business analytics is applied in order to offer an approach to transform real-world data to concrete operational decision support (action). The focus here is on the analysis step using a new set covering model with several essential restrictions integrated for the first time. A hybrid column generation approach is applied, which solves the pricing problem by means of a genetic algorithm. The artifact is evaluated with the help of a case study of three real-world transport networks. It is shown that the hybrid solution approach is able to solve the problem more effectively and efficiently compared to conventional approaches used in practice.

Suggested Citation

  • Kirsten Hoffmann & Udo Buscher & Janis Sebastian Neufeld & Felix Tamke, 2017. "Solving Practical Railway Crew Scheduling Problems with Attendance Rates," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(3), pages 147-159, June.
    • Handle: RePEc:spr:binfse:v:59:y:2017:i:3:d:10.1007_s12599-017-0470-8
    DOI: 10.1007/s12599-017-0470-8
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    References listed on IDEAS

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    Cited by:

    1. Scheffler, Martin & Neufeld, Janis S. & Hölscher, Michael, 2020. "An MIP-based heuristic solution approach for the locomotive assignment problem focussing on (dis-)connecting processes," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 64-80.
    2. Zhengcai Cao & Lijie Zhou & Biao Hu & Chengran Lin, 2019. "An Adaptive Scheduling Algorithm for Dynamic Jobs for Dealing with the Flexible Job Shop Scheduling Problem," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 299-309, June.
    3. Neufeld, Janis S. & Scheffler, Martin & Tamke, Felix & Hoffmann, Kirsten & Buscher, Udo, 2021. "An efficient column generation approach for practical railway crew scheduling with attendance rates," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1113-1130.
    4. Heil, Julia & Hoffmann, Kirsten & Buscher, Udo, 2020. "Railway crew scheduling: Models, methods and applications," European Journal of Operational Research, Elsevier, vol. 283(2), pages 405-425.

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