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Robust Train Timetabling

In: Handbook of Optimization in the Railway Industry

Author

Listed:
  • Valentina Cacchiani

    (DEI, University of Bologna)

  • Paolo Toth

    (DEI, University of Bologna)

Abstract

Nowadays railway systems are highly affected by disturbances, occurring in daily operations, and causing train delays and passenger inconvenience. Not only they negatively affect the passengers satisfaction, but they also cause additional operational costs, since the planned schedule needs to be modified in real-time. Train timetabling is a particularly critical phase in railway system management, since, in real-time operations, all the changes applied to the planned timetable impact on platform assignment, rolling stock circulation and crew scheduling. Therefore, in the strategic planning, it is an important issue to determine robust timetables, i.e., timetables that “perform well” under disturbances, avoiding delay propagation as much as possible. In this chapter, we present state-of-the-art methods that achieve robust timetables, and discuss their advantages and drawbacks.

Suggested Citation

  • Valentina Cacchiani & Paolo Toth, 2018. "Robust Train Timetabling," International Series in Operations Research & Management Science, in: Ralf Borndörfer & Torsten Klug & Leonardo Lamorgese & Carlo Mannino & Markus Reuther & Thomas Schlec (ed.), Handbook of Optimization in the Railway Industry, chapter 0, pages 93-115, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-72153-8_5
    DOI: 10.1007/978-3-319-72153-8_5
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    Citations

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    Cited by:

    1. Pu, Song & Zhan, Shuguang, 2021. "Two-stage robust railway line-planning approach with passenger demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    2. 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.
    3. Cacchiani, Valentina & Qi, Jianguo & Yang, Lixing, 2020. "Robust optimization models for integrated train stop planning and timetabling with passenger demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 1-29.
    4. Oddvar Kloster & Bjørnar Luteberget & Carlo Mannino & Giorgio Sartor, 2023. "An Optimization-Based Decision Support Tool for Incremental Train Timetabling," SN Operations Research Forum, Springer, vol. 4(3), pages 1-20, September.
    5. Franciszek Restel & Łukasz Wolniewicz & Matea Mikulčić, 2021. "Method for Designing Robust and Energy Efficient Railway Schedules," Energies, MDPI, vol. 14(24), pages 1-12, December.
    6. Sartor, Giorgio & Mannino, Carlo & Nygreen, Thomas & Bach, Lukas, 2023. "A MILP model for quasi-periodic strategic train timetabling," Omega, Elsevier, vol. 116(C).

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