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Disruption Management of Rolling Stock in Passenger Railway Transportation

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  • Nielsen, L.K.
  • Maróti, G.

Abstract

This paper deals with real-time disruption management of rolling stock in passenger railway transportation. We present a generic framework for modeling disruptions in railway rolling stock schedules. The framework is presented as an online combinatorial decision problem where the uncertainty of a disruption is modeled by a sequence of information updates. To decompose the problem we propose a rolling horizon approach where only rolling stock decisions within a certain time horizon from the time of rescheduling are taken into account. The schedules are then revised as the situation progresses and more accurate information becomes available. We extend an existing model for rolling stock scheduling to the specific requirements of the real-time case and apply it in the rolling horizon framework. We perform computational tests on instances constructed from real life cases and explore the consequences of different settings of the approach for the trade-off between solution quality and computation time.

Suggested Citation

  • 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.
  • Handle: RePEc:ems:eureri:16557
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    References listed on IDEAS

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    1. Törnquist, Johanna, 2007. "Railway traffic disturbance management--An experimental analysis of disturbance complexity, management objectives and limitations in planning horizon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(3), pages 249-266, March.
    2. 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.
    3. Budai-Balke, G. & Maróti, G. & Dekker, R. & Huisman, D. & Kroon, L.G., 2007. "Re-scheduling in railways: the rolling stock balancing problem," Econometric Institute Research Papers EI 2007-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    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.
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    Cited by:

    1. Haahr, Jørgen T. & Wagenaar, Joris C. & Veelenturf, Lucas P. & Kroon, Leo G., 2016. "A comparison of two exact methods for passenger railway rolling stock (re)scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 15-32.
    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.
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    7. Wagenaar, Joris & Kroon, Leo & Fragkos, Ioannis, 2017. "Rolling stock rescheduling in passenger railway transportation using dead-heading trips and adjusted passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 140-161.
    8. Wang, Yihui & Zhao, Kangqi & D’Ariano, Andrea & Niu, Ru & Li, Shukai & Luan, Xiaojie, 2021. "Real-time integrated train rescheduling and rolling stock circulation planning for a metro line under disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 87-117.
    9. 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.
    10. 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.
    11. Mo, Baichuan & Koutsopoulos, Haris N. & Shen, Zuo-Jun Max & Zhao, Jinhua, 2023. "Robust path recommendations during public transit disruptions under demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 82-107.
    12. Lusby, Richard M. & Haahr, Jørgen Thorlund & Larsen, Jesper & Pisinger, David, 2017. "A Branch-and-Price algorithm for railway rolling stock rescheduling," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 228-250.
    13. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    14. Gedik, Ridvan & Medal, Hugh & Rainwater, Chase & Pohl, Ed A. & Mason, Scott J., 2014. "Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 45-57.
    15. Wang, Xuekai & D’Ariano, Andrea & Su, Shuai & Tang, Tao, 2023. "Cooperative train control during the power supply shortage in metro system: A multi-agent reinforcement learning approach," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 244-278.

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    More about this item

    Keywords

    combinatorial decision problem; disruptions; passenger railway transportation;
    All these keywords.

    JEL classification:

    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R19 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Other
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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