IDEAS home Printed from https://ideas.repec.org/a/taf/tjsmxx/v12y2018i1p53-66.html
   My bibliography  Save this article

A simheuristic algorithm for solving the arc routing problem with stochastic demands

Author

Listed:
  • Sergio Gonzalez-Martin
  • Angel A. Juan
  • Daniel Riera
  • Monica G. Elizondo
  • Juan J. Ramos

Abstract

This paper proposes a simheuristic algorithm for solving the Arc Routing Problem with Stochastic Demands. Our approach combines Monte Carlo Simulation (MCS) with the RandSHARP metaheuristic, which was originally designed for solving the Capacitated Arc Routing Problem with deterministic demands (CARP). The RandSHARP metaheuristic is a biased-randomised version of a savings-based heuristic for the CARP, which allows it to obtain competitive results for this problem in low computational times. The RandSHARP is then combined with MCS to cope with the stochastic variant of the problem in a natural and efficient way. Our work is based on the use of a safety stock during the route-design stage. This safety stock can then be used during the delivery stage to satisfy unexpected demands. A reliability index is also defined to evaluate the robustness of each solution with respect to possible route failures caused by random demands. Some numerical experiments contribute to validate our approach and to illustrate its potential benefits.

Suggested Citation

  • Sergio Gonzalez-Martin & Angel A. Juan & Daniel Riera & Monica G. Elizondo & Juan J. Ramos, 2018. "A simheuristic algorithm for solving the arc routing problem with stochastic demands," Journal of Simulation, Taylor & Francis Journals, vol. 12(1), pages 53-66, January.
    • Handle: RePEc:taf:tjsmxx:v:12:y:2018:i:1:p:53-66
    DOI: 10.1057/jos.2016.11
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1057/jos.2016.11
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/jos.2016.11?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. Victor Abu-Marrul & Rafael Martinelli & Silvio Hamacher & Irina Gribkovskaia, 2023. "Simheuristic algorithm for a stochastic parallel machine scheduling problem with periodic re-planning assessment," Annals of Operations Research, Springer, vol. 320(2), pages 547-572, January.
    2. Yagmur S. Gök & Silvia Padrón & Maurizio Tomasella & Daniel Guimarans & Cemalettin Ozturk, 2023. "Constraint-based robust planning and scheduling of airport apron operations through simheuristics," Annals of Operations Research, Springer, vol. 320(2), pages 795-830, January.
    3. Angel A. Juan & Peter Keenan & Rafael Martí & Seán McGarraghy & Javier Panadero & Paula Carroll & Diego Oliva, 2023. "A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics," Annals of Operations Research, Springer, vol. 320(2), pages 831-861, January.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tjsmxx:v:12:y:2018:i:1:p:53-66. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjsm .

    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.