IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v121y2025i17d10.1007_s11069-025-07598-1.html
   My bibliography  Save this article

Picture fuzzy decision support system–weighted p‑median framework for disaster emergency center siting in the Philippines

Author

Listed:
  • İbrahim Miraç ELİGÜZEL

    (Gaziantep Islam Science and Technology University)

Abstract

This study presents an innovative decision support system aimed at addressing the challenges of uncertainty and resource allocation in disaster management. In addition, the Philippines is presented as a case study to demonstrate its practical implementation and validate its effectiveness. The core of the methodology is based on Picture Fuzzy Sets (PFSs). PFSs are utilized to represent and consolidate linguistic uncertainty associated with different hazard categories. Essential methodologies encompass the calculation of Hamming distances, product-based aggregation operators, Z-score normalization, and a softmax-based weighting approach. These methods collectively convert raw disaster data into substantial disaster-specific weights. A weighted p-median approach is utilized to optimize the allocation of emergency operational centers. While the methodology is broadly applicable, the results confirm that the proposed approach offers a flexible and precise tool for multi-criteria decision support in disaster management.

Suggested Citation

  • İbrahim Miraç ELİGÜZEL, 2025. "Picture fuzzy decision support system–weighted p‑median framework for disaster emergency center siting in the Philippines," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(17), pages 20171-20192, October.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:17:d:10.1007_s11069-025-07598-1
    DOI: 10.1007/s11069-025-07598-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-025-07598-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-025-07598-1?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:spr:nathaz:v:121:y:2025:i:17:d:10.1007_s11069-025-07598-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.