IDEAS home Printed from https://ideas.repec.org/a/taf/tjmaxx/v8y2021i3p443-485.html
   My bibliography  Save this article

Crowd evacuation simulation model with soft computing optimization techniques: a systematic literature review

Author

Listed:
  • Hamizan Sharbini
  • Roselina Sallehuddin
  • Habibollah Haron

Abstract

Crowd evacuation simulation is an essential element when it comes to planning and preparation in evacuation management. This paper presents the survey based on systematic literature review (SLR) technique that aims to identify the crowd evacuation under microscopic model integrated with soft computing technique from previous works. In the review process, renowned databases were searched to retrieve the primary articles and total 38 studies were thoroughly studied. The researcher has identified the potential optimization factors in simulating crowd evacuation and research gaps based on acquired issues, limitation and challenges in this domain. The results of this SLR will serve as a guideline for the researchers that have same interest to develop better and effective crowd evacuation simulation model. The future direction from this SLR also suggests that there is a potential to hybrid the model with soft-computing optimization focusing on latest nature-inspired algorithms in improving the crowd evacuation model.

Suggested Citation

  • Hamizan Sharbini & Roselina Sallehuddin & Habibollah Haron, 2021. "Crowd evacuation simulation model with soft computing optimization techniques: a systematic literature review," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(3), pages 443-485, July.
  • Handle: RePEc:taf:tjmaxx:v:8:y:2021:i:3:p:443-485
    DOI: 10.1080/23270012.2021.1881924
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23270012.2021.1881924
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23270012.2021.1881924?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.

    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:tjmaxx:v:8:y:2021:i:3:p:443-485. 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/tjma .

    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.