IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v270y2018i3p968-981.html
   My bibliography  Save this article

A minmax regret version of the time-dependent shortest path problem

Author

Listed:
  • Conde, Eduardo
  • Leal, Marina
  • Puerto, Justo

Abstract

We consider a shortest path problem where the arc costs depend on their relative position on the given path and there exist uncertain cost parameters. We study a minmax regret version of the problem under different types of uncertainty of the involved parameters. First, we provide a Mixed Integer Linear Programming (MILP) formulation by using strong duality in the uncertainty interval case. Second, we develop three algorithms based on Benders decomposition for general polyhedral sets of uncertainty. In order to make the algorithms faster we use constant factor approximations to initialize them. Finally, we report some computational experiments for different uncertainty sets in order to compare the behavior of the proposed algorithms.

Suggested Citation

  • Conde, Eduardo & Leal, Marina & Puerto, Justo, 2018. "A minmax regret version of the time-dependent shortest path problem," European Journal of Operational Research, Elsevier, vol. 270(3), pages 968-981.
    • Handle: RePEc:eee:ejores:v:270:y:2018:i:3:p:968-981
    DOI: 10.1016/j.ejor.2018.04.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221718303333
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2018.04.030?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. Luo, Chunling & Tan, Chin Hon & Liu, Xiao, 2020. "Maximum excess dominance: Identifying impractical solutions in linear problems with interval coefficients," European Journal of Operational Research, Elsevier, vol. 282(2), pages 660-676.
    2. Víctor Blanco & Ricardo Gázquez & Marina Leal, 2023. "Mathematical optimization models for reallocating and sharing health equipment in pandemic situations," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 355-390, July.

    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:270:y:2018:i:3:p:968-981. 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.