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An Iterative Framework for Real-time Railway Rescheduling

Author

Listed:
  • Dollevoet, T.A.B.
  • Huisman, D.
  • Kroon, L.G.
  • Veelenturf, L.P.
  • Wagenaar, J.C.

Abstract

Since disruptions in railway networks are inevitable, railway operators and infrastructure managers need reliable measures and tools for disruption management. Current literature on railway disruption management focuses most of the time on rescheduling one resource (timetable, rolling stock or crew) at the time. In this research, we describe an iterative framework in which all three resources are considered. The framework applies existing models and algorithms for rescheduling the individual resources. We extensively test our framework on instances from Netherlands Railways and show that schedules which are feasible for all three resources can be obtained within short computation times. This shows that the framework and the existing rescheduling approaches can be of great value in practice.

Suggested Citation

  • Dollevoet, T.A.B. & Huisman, D. & Kroon, L.G. & Veelenturf, L.P. & Wagenaar, J.C., 2015. "An Iterative Framework for Real-time Railway Rescheduling," Econometric Institute Research Papers EI2015-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:78719
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    References listed on IDEAS

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    1. Potthoff, D. & Huisman, D. & Desaulniers, G., 2008. "Column generation with dynamic duty selection for railway crew rescheduling," Econometric Institute Research Papers EI 2008-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Nielsen, Lars Kjær & Kroon, Leo & Maróti, Gábor, 2012. "A rolling horizon approach for disruption management of railway rolling stock," European Journal of Operational Research, Elsevier, vol. 220(2), pages 496-509.
    3. Daniel Potthoff & Dennis Huisman & Guy Desaulniers, 2010. "Column Generation with Dynamic Duty Selection for Railway Crew Rescheduling," Transportation Science, INFORMS, vol. 44(4), pages 493-505, November.
    4. Fioole, Pieter-Jan & Kroon, Leo & Maroti, Gabor & Schrijver, Alexander, 2006. "A rolling stock circulation model for combining and splitting of passenger trains," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1281-1297, October.
    5. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    6. D'Ariano, Andrea & Pacciarelli, Dario & Pranzo, Marco, 2007. "A branch and bound algorithm for scheduling trains in a railway network," European Journal of Operational Research, Elsevier, vol. 183(2), pages 643-657, December.
    7. Veelenturf, L.P. & Potthoff, D. & Huisman, D. & Kroon, L.G., 2009. "Railway Crew Rescheduling with Retiming," Econometric Institute Research Papers EI 2009-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Zhan, Shuguang & Kroon, Leo G. & Veelenturf, Lucas P. & Wagenaar, Joris C., 2015. "Real-time high-speed train rescheduling in case of a complete blockage," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 182-201.
    9. Leonardo Lamorgese & Carlo Mannino, 2015. "An Exact Decomposition Approach for the Real-Time Train Dispatching Problem," Operations Research, INFORMS, vol. 63(1), pages 48-64, February.
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    Cited by:

    1. Hoogervorst, R. & Dollevoet, T.A.B. & Maróti, G. & Huisman, D., 2018. "Reducing Passenger Delays by Rolling Stock Rescheduling," Econometric Institute Research Papers EI2018-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Biao Yuan & Zhibin Jiang, 2017. "Disruption Management for the Real-Time Home Caregiver Scheduling and Routing Problem," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    3. Dekker, M.M. & van Lieshout, R.N. & Ball, R.C. & Bouman, P.C. & Dekker, S.C. & Dijkstra, H.A. & Goverde, R.M.P. & Huisman, D. & Panja, D. & Schaafsma, A.M. & van den Akker, M., 2018. "A Next Step in Disruption Management: Combining Operations Research and Complexity Science," Econometric Institute Research Papers EI2018-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    Keywords

    Railway Operations; Disruption Management; Algorithmic Framework;
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