IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v280y2020i3p953-969.html
   My bibliography  Save this article

Recovery management for a dial-a-ride system with real-time disruptions

Author

Listed:
  • Paquay, Célia
  • Crama, Yves
  • Pironet, Thierry

Abstract

The problem considered in this work stems from a non-profit organization in charge of door-to-door passenger transportation for medical appointments. Patients are picked up at home by a driver and are then dropped at their appointment location. They may also be driven back home at the end of their appointment. Some patients have specific requirements, e.g., they may require an accompanying person or a wheelchair. Planning such activities gives rise to a so-called dial-a-ride problem. In the present work, it is assumed that the requests assigned to the drivers have been selected, and the transportation plan has been established for the next day. However, in practice, appointment durations may vary due to unforeseen circumstances, and some transportation requests may be modified, delayed or canceled during the day. The aim of this work is to propose a reactive algorithm which can adapt the initial plan in order to manage the disruptions and to take care of as many patients as possible in real-time. The plan should be modified quickly when a perturbation is observed, without resorting to major changes which may confuse the drivers and the patients. Several recourse procedures are defined for this purpose. They allow the dispatcher to temporarily delete a request, to insert a previously deleted request, or to permanently cancel a request. Simulation techniques are used to test the approach on randomly generated scenarios. Several key performance indicators are introduced in order to measure the impact of the disruptions and the quality of the solutions.

Suggested Citation

  • Paquay, Célia & Crama, Yves & Pironet, Thierry, 2020. "Recovery management for a dial-a-ride system with real-time disruptions," European Journal of Operational Research, Elsevier, vol. 280(3), pages 953-969.
  • Handle: RePEc:eee:ejores:v:280:y:2020:i:3:p:953-969
    DOI: 10.1016/j.ejor.2019.08.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221719306599
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2019.08.006?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yan, Pengyu & Yu, Kaize & Chao, Xiuli & Chen, Zhibin, 2023. "An online reinforcement learning approach to charging and order-dispatching optimization for an e-hailing electric vehicle fleet," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1218-1233.
    2. Wang, Hongfei & Guan, Hongzhi & Qin, Huanmei & Zhao, Pengfei, 2024. "Assessing the sustainability of time-dependent electric demand responsive transit service through deep reinforcement learning," Energy, Elsevier, vol. 296(C).
    3. Lian, Ying & Lucas, Flavien & Sörensen, Kenneth, 2024. "Prepositioning can improve the performance of a dynamic stochastic on-demand public bus system," European Journal of Operational Research, Elsevier, vol. 312(1), pages 338-356.
    4. Zhang, Zhenyu & Ji, Tingting & Wei, Hsi-Hsien, 2022. "Dynamic emergency inspection routing and restoration scheduling to enhance the post-earthquake resilience of a highway–bridge network," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    5. Sinha, Priyank & Kumar, Sameer & Chandra, Charu, 2023. "Strategies for ensuring required service level for COVID-19 herd immunity in Indian vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 304(1), pages 339-352.
    6. Guo, Yuhan & Zhang, Yu & Boulaksil, Youssef, 2021. "Real-time ride-sharing framework with dynamic timeframe and anticipation-based migration," European Journal of Operational Research, Elsevier, vol. 288(3), pages 810-828.
    7. Molenbruch, Yves & Braekers, Kris & Hirsch, Patrick & Oberscheider, Marco, 2021. "Analyzing the benefits of an integrated mobility system using a matheuristic routing algorithm," European Journal of Operational Research, Elsevier, vol. 290(1), pages 81-98.

    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:eee:ejores:v:280:y:2020:i:3:p:953-969. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.