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Railway crew scheduling: Models, methods and applications

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  • Heil, Julia
  • Hoffmann, Kirsten
  • Buscher, Udo

Abstract

The railway crew scheduling problem consists of finding the most efficient duty combination for railway crews to cover all trains and related activities for a defined period of time. Crew scheduling problems in transportation originate in airline and bus industries. In the 1990s, researchers developed sophisticated algorithms which were capable of solving the larger and more complex problem instances of railway operators. Practical implementations and decision support tools received very satisfying feedback from the industry. Since then, numerous real-world problems have been studied requiring innovative algorithmic approaches to the NP-hard problem. In this paper, we review 123 articles on railway crew scheduling focusing on more recent publications since 2000. After depicting crew scheduling in railway including the differences between transportation modes, our goal is to classify the literature according to model formulations, objectives, constraints and solution methods. By systematizing the collected articles, we identify research opportunities including integrated approaches with other planning stages, real-time re-scheduling and a further investigation of the impact of robustness and employee satisfaction on the cost of railway crew schedules.

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  • 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.
    • Handle: RePEc:eee:ejores:v:283:y:2020:i:2:p:405-425
    DOI: 10.1016/j.ejor.2019.06.016
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    2. 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.
    3. Pan, Hanchuan & Liu, Zhigang & Yang, Lixing & Liang, Zhe & Wu, Qiang & Li, Sijie, 2021. "A column generation-based approach for integrated vehicle and crew scheduling on a single metro line with the fully automatic operation system by partial supervision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. Fei Peng & Xian Fan & Puxin Wang & Mingan Sheng, 2022. "A Time-Space Network-Based Optimization Method for Scheduling Depot Drivers," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
    5. Ammann, Pia & Kolisch, Rainer & Schiffer, Maximilian, 2023. "Driver routing and scheduling with synchronization constraints," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    6. Thomas Breugem & Twan Dollevoet & Dennis Huisman, 2022. "Is Equality Always Desirable? Analyzing the Trade-Off Between Fairness and Attractiveness in Crew Rostering," Management Science, INFORMS, vol. 68(4), pages 2619-2641, April.
    7. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.

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