IDEAS home Printed from https://ideas.repec.org/a/spr/pubtra/v12y2020i2d10.1007_s12469-020-00232-2.html
   My bibliography  Save this article

Coordinating maintenance windows and train traffic: a case study

Author

Listed:
  • Tomas Lidén

    (Linköping University, Department of Science and Technology
    Swedish National Road and Transport Resarch Institute, Traffic Analysis and Logistics)

Abstract

This paper concerns a case study for optimal planning and coordination of railway maintenance windows and train traffic. The purpose is to validate a previously presented optimization model on a demanding real-life problem instance and to obtain results that apply in similar planning situations. A mixed integer linear programming model is used for a 913 km long, single-track railway line through the northern part of Sweden, with traffic consisting of 82 trains per day, most of which are freight trains. Cyclic 1-day schedules are produced, which show that 2 h long maintenance windows can be scheduled with small adjustments of the train traffic. The sensitivity for cost changes is studied, which shows that the train costs must increase by more than 30% in order to change the structure of the window solutions. Resource efficient window schedules are obtained by assigning maintenance teams to all windows while respecting crew work and rest time restrictions. A comparison with manually constructed plans from the Swedish Transport Administration indicates that larger window volumes can be scheduled at a lower cost and with solution structures which are deemed reasonable and useful as guidance for constructing the real window patterns. Finally, we estimate that using an integrated planning approach (where maintenance and trains are jointly planned) instead of a sequential approach (where a train timetable has precedence over the maintenance windows), will give maintenance cost savings of 11–17%, without incurring any large cost increases for the train traffic. The paper also presents a method for achieving cyclic schedules without any period-deciding variables, and discusses the consequences of the aggregated capacity usage model that has been adopted.

Suggested Citation

  • Tomas Lidén, 2020. "Coordinating maintenance windows and train traffic: a case study," Public Transport, Springer, vol. 12(2), pages 261-298, June.
    • Handle: RePEc:spr:pubtra:v:12:y:2020:i:2:d:10.1007_s12469-020-00232-2
    DOI: 10.1007/s12469-020-00232-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12469-020-00232-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12469-020-00232-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. G Budai & D Huisman & R Dekker, 2006. "Scheduling preventive railway maintenance activities," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1035-1044, September.
    2. Valentina Cacchiani & Alberto Caprara & Laura Galli & Leo Kroon & Gábor Maróti & Paolo Toth, 2012. "Railway Rolling Stock Planning: Robustness Against Large Disruptions," Transportation Science, INFORMS, vol. 46(2), pages 217-232, May.
    3. J. I. van Zante--de Fokkert & D. den Hertog & F. J. van den Berg & J. H. M. Verhoeven, 2007. "The Netherlands Schedules Track Maintenance to Improve Track Workers’ Safety," Interfaces, INFORMS, vol. 37(2), pages 133-142, April.
    4. Lucas P. Veelenturf & Martin P. Kidd & Valentina Cacchiani & Leo G. Kroon & Paolo Toth, 2016. "A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions," Transportation Science, INFORMS, vol. 50(3), pages 841-862, August.
    5. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    6. Natashia Boland & Mike Hewitt & Luke Marshall & Martin Savelsbergh, 2019. "The price of discretizing time: a study in service network design," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(2), pages 195-216, June.
    7. Maurice QUEYRANNE & Laurence A. WOLSEY, 2017. "Tight MIP formulations for bounded up/down times and interval-dependent start-ups," LIDAM Reprints CORE 2876, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Peter Brucker & Silvia Heitmann & Sigrid Knust, 2005. "Scheduling railway traffic at a construction site," Springer Books, in: Hans-Otto Günther & Kap Hwan Kim (ed.), Container Terminals and Automated Transport Systems, pages 345-356, Springer.
    9. Peng, Fan & Ouyang, Yanfeng, 2012. "Track maintenance production team scheduling in railroad networks," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1474-1488.
    10. Wen, M. & Li, R. & Salling, K.B., 2016. "Optimization of preventive condition-based tamping for railway tracks," European Journal of Operational Research, Elsevier, vol. 252(2), pages 455-465.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sedghi, Mahdieh & Kauppila, Osmo & Bergquist, Bjarne & Vanhatalo, Erik & Kulahci, Murat, 2021. "A taxonomy of railway track maintenance planning and scheduling: A review and research trends," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. Zhang, Chuntian & Gao, Yuan & Yang, Lixing & Gao, Ziyou & Qi, Jianguo, 2020. "Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 64-92.
    3. Lusby, Richard M. & Larsen, Jesper & Bull, Simon, 2018. "A survey on robustness in railway planning," European Journal of Operational Research, Elsevier, vol. 266(1), pages 1-15.
    4. Wang, Jiaxi, 2024. "Maintenance scheduling at high-speed train depots: An optimization approach," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    5. Vansteenwegen, Pieter & Dewilde, Thijs & Burggraeve, Sofie & Cattrysse, Dirk, 2016. "An iterative approach for reducing the impact of infrastructure maintenance on the performance of railway systems," European Journal of Operational Research, Elsevier, vol. 252(1), pages 39-53.
    6. Eva König, 2020. "A review on railway delay management," Public Transport, Springer, vol. 12(2), pages 335-361, June.
    7. M. Shakibayifar & A. Sheikholeslami & F. Corman & E. Hassannayebi, 2020. "An integrated rescheduling model for minimizing train delays in the case of line blockage," Operational Research, Springer, vol. 20(1), pages 59-87, March.
    8. Peng, Fan & Ouyang, Yanfeng, 2012. "Track maintenance production team scheduling in railroad networks," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1474-1488.
    9. Budai-Balke, G. & Dekker, R. & Kaymak, U., 2009. "Genetic and memetic algorithms for scheduling railway maintenance activities," Econometric Institute Research Papers EI 2009-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Francisco A. Ortega & Miguel A. Pozo & Justo Puerto, 2018. "On-Line Timetable Rescheduling in a Transit Line," Transportation Science, INFORMS, vol. 52(5), pages 1106-1121, October.
    11. 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.
    12. Liping Ge & Stefan Voß & Lin Xie, 2022. "Robustness and disturbances in public transport," Public Transport, Springer, vol. 14(1), pages 191-261, March.
    13. Polinder, Gert-Jaap & Breugem, Thomas & Dollevoet, Twan & Maróti, Gábor, 2019. "An adjustable robust optimization approach for periodic timetabling," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 50-68.
    14. Baldi, Mauro M. & Heinicke, Franziska & Simroth, Axel & Tadei, Roberto, 2016. "New heuristics for the Stochastic Tactical Railway Maintenance Problem," Omega, Elsevier, vol. 63(C), pages 94-102.
    15. Mohammadi, Reza & He, Qing & Karwan, Mark, 2021. "Data-driven robust strategies for joint optimization of rail renewal and maintenance planning," Omega, Elsevier, vol. 103(C).
    16. Zhang, Chuntian & Gao, Yuan & Yang, Lixing & Kumar, Uday & Gao, Ziyou, 2019. "Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors," Omega, Elsevier, vol. 87(C), pages 86-104.
    17. Van Aken, Sander & Bešinović, Nikola & Goverde, Rob M.P., 2017. "Designing alternative railway timetables under infrastructure maintenance possessions," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 224-238.
    18. Alice Consilvio & Angela Febbraro & Rossella Meo & Nicola Sacco, 2019. "Risk-based optimal scheduling of maintenance activities in a railway network," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 435-465, December.
    19. 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).
    20. Ji, Hangyu & Wang, Rui & Zhang, Chuntian & Yin, Jiateng & Ma, Lin & Yang, Lixing, 2024. "Optimization of train schedule with uncertain maintenance plans in high-speed railways: A stochastic programming approach," Omega, Elsevier, vol. 124(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:pubtra:v:12:y:2020:i:2:d:10.1007_s12469-020-00232-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.