IDEAS home Printed from https://ideas.repec.org/a/igg/jfsa00/v14y2025i1p1-25.html
   My bibliography  Save this article

A Group Decision-Making Method With Probabilistic Linguistic Preference Relations Based on Additive Consistency and Its Application

Author

Listed:
  • Feng Wang

    (Guangdong University of Finance and Economics, China)

  • Qingfan Zhang

    (Guangdong University of Finance and Economics, China)

  • Xi Han

    (Guangdong University of Finance and Economics, China)

Abstract

How to evaluate the citizens' sense of gain (CSG) is an essential problem in the new smart city. To solve the problem, this paper investigates a group decision making (GDM) method with probabilistic linguistic preference relations (PLPRs). First, the additive consistency of PLPR is defined by the linguistic hybrid weighted average (LHWA) operator. The LHWA-based linguistic preference relation is extracted from a PLPR to derive the priority weights. For the GDM problem in the linguistic environment, combining the linguistic evaluations and their probability of different citizens, i.e, decision makers (DMs), the PLPRs of DMs' subsets (DMSes) are formed to obtain the corresponding priority weights. The similarity divergences and the proximity divergences of DMSes are introduced to derive DMSes' weights. Using the relative entropy, the comprehensive priority weights are generated for ranking alternatives. Thus, a GDM method with PLPRs is proposed and validated.

Suggested Citation

  • Feng Wang & Qingfan Zhang & Xi Han, 2025. "A Group Decision-Making Method With Probabilistic Linguistic Preference Relations Based on Additive Consistency and Its Application," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 14(1), pages 1-25, January.
  • Handle: RePEc:igg:jfsa00:v:14:y:2025:i:1:p:1-25
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJFSA.371416
    Download Restriction: no
    ---><---

    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:jfsa00:v:14:y:2025:i:1:p:1-25. 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: 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.