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Disruption management in passenger railway transportation

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  • Jespersen-Groth, J.
  • Potthoff, D.
  • Clausen, J.
  • Huisman, D.
  • Kroon, L.G.
  • Maróti, G.
  • Nielsen, M.N.

Abstract

This paper deals with disruption management in passenger railway transportation. In the disruption management process, many actors belonging to different organizations play a role. In this paper we therefore describe the process itself and the roles of the different actors. Furthermore, we discuss the three main subproblems in railway disruption management: timetable adjustment, and rolling stock and crew re-scheduling. Next to a general description of these problems, we give an overview of the existing literature and we present some details of the specific situations at DSB S-tog and NS. These are the railway operators in the suburban area of Copenhagen, Denmark, and on the main railway lines in the Netherlands, respectively. Since not much research has been carried out yet on Operations Research models for disruption management in the railway context, models and techniques that have been developed for related problems in the airline world are discussed as well. Finally, we address the integration of the re-scheduling processes of the timetable, and the resources rolling stock and crew.

Suggested Citation

  • Jespersen-Groth, J. & Potthoff, D. & Clausen, J. & Huisman, D. & Kroon, L.G. & Maróti, G. & Nielsen, M.N., 2007. "Disruption management in passenger railway transportation," Econometric Institute Research Papers EI 2007-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:8527
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    Cited by:

    1. 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.
    2. 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.
    3. Louwerse, Ilse & Huisman, Dennis, 2014. "Adjusting a railway timetable in case of partial or complete blockades," European Journal of Operational Research, Elsevier, vol. 235(3), pages 583-593.
    4. Sato, Keisuke & Fukumura, Naoto, 2012. "Real-time freight locomotive rescheduling and uncovered train detection during disruption," European Journal of Operational Research, Elsevier, vol. 221(3), pages 636-648.
    5. Acuna-Agost, Rodrigo & Michelon, Philippe & Feillet, Dominique & Gueye, Serigne, 2011. "SAPI: Statistical Analysis of Propagation of Incidents. A new approach for rescheduling trains after disruptions," European Journal of Operational Research, Elsevier, vol. 215(1), pages 227-243, November.
    6. Paul Davidsson & Banafsheh Hajinasab & Johan Holmgren & Åse Jevinger & Jan A. Persson, 2016. "The Fourth Wave of Digitalization and Public Transport: Opportunities and Challenges," Sustainability, MDPI, vol. 8(12), pages 1-16, November.
    7. Evelien van der Hurk & Haris N. Koutsopoulos & Nigel Wilson & Leo G. Kroon & Gábor Maróti, 2016. "Shuttle Planning for Link Closures in Urban Public Transport Networks," Transportation Science, INFORMS, vol. 50(3), pages 947-965, August.
    8. Nielsen, L.K. & Maróti, G., 2009. "Disruption Management of Rolling Stock in Passenger Railway Transportation," ERIM Report Series Research in Management ERS-2009-046-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    9. Jian Gang Jin & Kwong Meng Teo & Amedeo R. Odoni, 2016. "Optimizing Bus Bridging Services in Response to Disruptions of Urban Transit Rail Networks," Transportation Science, INFORMS, vol. 50(3), pages 790-804, August.
    10. Lucas P. Veelenturf & Daniel Potthoff & Dennis Huisman & Leo G. Kroon & Gábor Maróti & Albert P. M. Wagelmans, 2016. "A Quasi-Robust Optimization Approach for Crew Rescheduling," Transportation Science, INFORMS, vol. 50(1), pages 204-215, February.
    11. Cacchiani, V. & Huisman, D. & Kidd, M.P. & Kroon, L.G. & Toth, P. & Veelenturf, L.P. & Wagenaar, J.C., 2013. "An Overview of Recovery Models for Real-time Railway Rescheduling," Econometric Institute Research Papers 50112, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Kroon, L.G. & Huisman, D., 2011. "Algorithmic Support for Disruption Management at Netherlands Railways," Econometric Institute Research Papers EI 2011-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Balázs Dávid & Miklós Krész, 2017. "The dynamic vehicle rescheduling problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 809-830, December.
    14. Yan, Yongze & Hong, Liu & He, Xiaozheng & Ouyang, Min & Peeta, Srinivas & Chen, Xueguang, 2017. "Pre-disaster investment decisions for strengthening the Chinese railway system under earthquakes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 39-59.
    15. Leo Kroon & Gábor Maróti & Lars Nielsen, 2015. "Rescheduling of Railway Rolling Stock with Dynamic Passenger Flows," Transportation Science, INFORMS, vol. 49(2), pages 165-184, May.
    16. Haahr, J.T. & Wagenaar, J.C. & Veelenturf, L.P. & Kroon, L.G., 2015. "A Comparison of Two Exact Methods for Passenger Railway Rolling Stock (Re)Scheduling," ERIM Report Series Research in Management ERS-2015-007-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    17. 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.
    18. Yajuan Deng & Xiaolei Ru & Ziqi Dou & Guohua Liang, 2018. "Design of Bus Bridging Routes in Response to Disruption of Urban Rail Transit," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
    19. 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.
    20. 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.
    21. Ralf Borndörfer & Berkan Erol & Thomas Graffagnino & Thomas Schlechte & Elmar Swarat, 2014. "Optimizing the Simplon railway corridor," Annals of Operations Research, Springer, vol. 218(1), pages 93-106, July.
    22. 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.
    23. van Lieshout, R.N. & Bouman, P.C. & Huisman, D., 2018. "Determining and Evaluating Alternative Line Plans in (Near) Out-of-Control Situations," Econometric Institute Research Papers EI2018-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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