IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i7p1186-d1627805.html
   My bibliography  Save this article

A Novel Group Decision-Making Method with Adjustment Willingness in a Distributed Hesitant Fuzzy Linguistic Environment

Author

Listed:
  • Xiao Liang

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Xiaoxia Xu

    (Research Center of Risk Management and Emergency Decision Making, School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Francisco Javier Cabrerizo

    (Andalusian Research Institute in Data Science and Computational Intelligence, Department of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain)

Abstract

This research aims to construct a group decision-making (GDM) method that considers decision makers’ (DMs’) willingness to adjust in a distributed hesitant fuzzy linguistic (DHFL) environment. First, to address the practical scenario where DMs may express preferences using multiple linguistic values with explicit preference strengths, this paper extends the distributed hesitant fuzzy linguistic preference relation (DHFLPR) and supplements missing probabilities. Second, we integrate multiplicative consistency and consensus within a DHFL environment to construct two preference optimization models, whose objective functions are to minimize the overall adjustment based on DMs’ willingness to adjust, thus making the decision more consistent with actual environments. Finally, the viability and effectiveness of the new method are validated by numerical examples. The results show that our new method allows individual preferences to quickly meet the consistency requirement while maximally preserving their original preferences. Additionally, the DHFLPRs maintain the fuzziness and hesitancy in the new preferences, and effectively address the issue of unequal importance among distinct linguistic preference values.

Suggested Citation

  • Xiao Liang & Xiaoxia Xu & Francisco Javier Cabrerizo, 2025. "A Novel Group Decision-Making Method with Adjustment Willingness in a Distributed Hesitant Fuzzy Linguistic Environment," Mathematics, MDPI, vol. 13(7), pages 1-22, April.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:7:p:1186-:d:1627805
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/7/1186/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/7/1186/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:7:p:1186-:d:1627805. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.