IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v14y2023i1p1-20.html
   My bibliography  Save this article

Firefighting Stations Allocation Model for the State of Kuwait

Author

Listed:
  • Hana O. A. Al-Omar

    (Kuwait University, Kuwait)

Abstract

The objective is to determine the best re-allocations of the stations to easily reach the accident location with both the least cost and time possible, with the best firefighting effective required facilities. This objective required dividing the six governorates into 133 areas served in 6 minutes efficient response time. The final findings of this study were 30 reallocated stations, which managed effectively to cover all 133 required areas. This has been shown on included maps of the six governorates. The goal linear programming model idea was not discussed in the emergency field research of the “State of Kuwait,” specifically in the firefighting emergency service. Moreover, this modeling can be expanded to cover all other types of emergency service topics such as health, paramedics, and police stations.

Suggested Citation

  • Hana O. A. Al-Omar, 2023. "Firefighting Stations Allocation Model for the State of Kuwait," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 14(1), pages 1-20, January.
    • Handle: RePEc:igg:joris0:v:14:y:2023:i:1:p:1-20
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJORIS.334126
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zeynep Gergin & Nükhet Tunçbilek & Şakir Esnaf, 2019. "Clustering Approach Using Artificial Bee Colony Algorithm for Healthcare Waste Disposal Facility Location Problem," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 10(1), pages 56-75, January.
    2. Raha Imanirad & Xin-She Yang & Julian Scott Yeomans, 2013. "A Concurrent Modelling to Generate Alternatives Approach Using the Firefly Algorithm," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 5(2), pages 33-45, April.
    3. Julian Scott Yeomans & Xin-She Yang, 2014. "Municipal waste management optimisation using a firefly algorithm-driven simulation-optimisation approach," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 4(4), pages 363-375.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:igg:joris0:v:14:y:2023:i:1:p:1-20. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

      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.