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Optimizing Railway Crew Scheduling at DB Schenker

Author

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  • Silke Jütte

    (Department of Supply Chain Management and Management Science, University of Cologne, D-50923 Cologne, Germany)

  • Marc Albers

    (Department of Supply Chain Management and Management Science, University of Cologne, D-50923 Cologne, Germany)

  • Ulrich W. Thonemann

    (Department of Supply Chain Management and Management Science, University of Cologne, D-50923 Cologne, Germany)

  • Knut Haase

    (Department of Transport Economics, University of Hamburg, D-20146 Hamburg, Germany)

Abstract

Freight railway crew scheduling consists of generating crew duties for operating trains on a schedule at minimal cost while meeting all work regulations and operational requirements. Typically, a freight railway operation uses thousands of trains and requires thousands of crew members to operate them. Because of the problem's large size, even moderate percentage savings in crew costs translate into large monetary savings. However, freight railway operations are complex, and a crew-scheduling problem is difficult to solve. We describe the development and implementation of crew-scheduling software at DB Schenker, the largest European railway freight carrier. The software is based on a column-generation solution technique. Computational results demonstrate that high-quality solutions can be obtained using reasonable run times, even for large problem instances. We implemented all of DB Schenker's major requirements to ensure that the software is operationally viable. Management also uses this software as a decision support tool for strategic planning.

Suggested Citation

  • Silke Jütte & Marc Albers & Ulrich W. Thonemann & Knut Haase, 2011. "Optimizing Railway Crew Scheduling at DB Schenker," Interfaces, INFORMS, vol. 41(2), pages 109-122, April.
    • Handle: RePEc:inm:orinte:v:41:y:2011:i:2:p:109-122
    DOI: 10.1287/inte.1100.0549
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    References listed on IDEAS

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    3. Michael F. Gorman & John-Paul Clarke & Amir Hossein Gharehgozli & Michael Hewitt & René de Koster & Debjit Roy, 2014. "State of the Practice: A Review of the Application of OR/MS in Freight Transportation," Interfaces, INFORMS, vol. 44(6), pages 535-554, December.
    4. Lusby, Richard M. & Larsen, Jesper & Bull, Simon, 2018. "A survey on robustness in railway planning," European Journal of Operational Research, Elsevier, vol. 266(1), pages 1-15.
    5. 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.
    6. 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.
    7. Suyabatmaz, Ali Çetin & Şahin, Güvenç, 2015. "Railway crew capacity planning problem with connectivity of schedules," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 88-100.
    8. 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.
    9. Jorge Amaya & Paula Uribe, 2018. "A model and computational tool for crew scheduling in train transportation of mine materials by using a local search strategy," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(3), pages 383-402, October.
    10. Silke Jütte & Daniel Müller & Ulrich W. Thonemann, 2017. "Optimizing railway crew schedules with fairness preferences," Journal of Scheduling, Springer, vol. 20(1), pages 43-55, February.
    11. Fuentes, Manuel & Cadarso, Luis & Marín, Ángel, 2019. "A hybrid model for crew scheduling in rail rapid transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 248-265.
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    13. Brian Roth & Anantaram Balakrishnan & Pooja Dewan & April Kuo & Dasaradh Mallampati & Juan Morales, 2018. "Crew Decision Assist: System for Optimizing Crew Assignments at BNSF Railway," Interfaces, INFORMS, vol. 48(5), pages 436-448, October.

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