IDEAS home Printed from https://ideas.repec.org/a/taf/tjsmxx/v10y2016i1p69-77.html
   My bibliography  Save this article

SimILS: a simulation-based extension of the iterated local search metaheuristic for stochastic combinatorial optimization

Author

Listed:
  • Alex Grasas
  • Angel A Juan
  • Helena R Lourenço

Abstract

Iterated Local Search (ILS) is one of the most popular single-solution-based metaheuristics. ILS is recognized by many authors as a relatively simple yet efficient framework able to deal with complex combinatorial optimization problems (COPs). ILS-based algorithms have been successfully applied to provide near-optimal solutions to different COPs in logistics, transportation, production, etc. However, ILS is designed to solve COPs under deterministic scenarios. In some real-life applications where uncertainty is present, the deterministic assumption makes the model less accurate since it does not reflect the real stochastic nature of the system. This paper presents the SimILS framework that extends ILS by integrating simulation to be able to cope with Stochastic COPs in a natural way. The paper also describes several tested applications that illustrate the main concepts behind SimILS and give rise to a new brand of ILS-based algorithms.

Suggested Citation

  • Alex Grasas & Angel A Juan & Helena R Lourenço, 2016. "SimILS: a simulation-based extension of the iterated local search metaheuristic for stochastic combinatorial optimization," Journal of Simulation, Taylor & Francis Journals, vol. 10(1), pages 69-77, February.
    • Handle: RePEc:taf:tjsmxx:v:10:y:2016:i:1:p:69-77
    DOI: 10.1057/jos.2014.25
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1057/jos.2014.25
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/jos.2014.25?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:10:y:2016:i:1:p:69-77. 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.