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Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods

Author

Listed:
  • Wei Liang

    (School of Economics and Management, Minjiang University, Fuzhou 350108, China
    Department of Computer Science, University of Jaén, 23071 Jaén, Spain)

  • Álvaro Labella

    (Department of Computer Science, University of Jaén, 23071 Jaén, Spain)

  • Meng-Jun Meng

    (School of Vocational Education, Shandong Youth University of Political Science, Jinan 250103, China)

  • Ying-Ming Wang

    (Decision Science Institute, School of Economics & Management, Fuzhou University, Fuzhou 350108, China)

  • Rosa M. Rodríguez

    (Department of Computer Science, University of Jaén, 23071 Jaén, Spain)

Abstract

The emergence and popularity of social media have made large-scale group decision-making (LSGDM) problems increasingly common, resulting in significant research interest in this field. LSGDM involves numerous evaluators, which can lead to disagreements and hesitancy among them. Hesitant fuzzy sets (HFSs) become crucial in this context as they capture the uncertainty and hesitancy among evaluators. On the other hand, research on the Consensus Reaching Process (CRP) becomes particularly important in dealing with the inevitable differences among the great number of evaluators. Ways to mitigate these differences to reach an agreement are a crucial area of study. For this reason, this paper presents a new CRP model to deal with LSGDM problems in hesitant fuzzy environments. First, HFSs and Normal-type Hesitant Fuzzy Sets (N-HFSs) are introduced to integrate evaluators’ subgroup and collective opinions, aiming to preserve as much decision information as possible while reducing computational complexity. Subsequently, a CRP with a detailed feedback suggestion generation mechanism is developed, which considers the willingness of evaluators to modify their opinions, thereby improving the effectiveness of reaching an agreement. Finally, a LSGDM framework that does not require any normalization process is proposed, and its feasibility and robustness are demonstrated through a numerical example.

Suggested Citation

  • Wei Liang & Álvaro Labella & Meng-Jun Meng & Ying-Ming Wang & Rosa M. Rodríguez, 2025. "Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods," Mathematics, MDPI, vol. 13(7), pages 1-28, April.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:7:p:1182-:d:1627579
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    References listed on IDEAS

    as
    1. Huchang Liao & Zeshui Xu & Meimei Xia, 2014. "Multiplicative Consistency Of Hesitant Fuzzy Preference Relation And Its Application In Group Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 47-76.
    2. Meng, Fanyong & Tang, Jie & An, Qingxian, 2023. "Cooperative game based two-stage consensus adjustment mechanism for large-scale group decision making," Omega, Elsevier, vol. 117(C).
    3. Kaixin Gong & Weimin Ma & Wenjing Lei & Mark Goh, 2024. "A dynamic trust network and influence measure-based consensus model for large-scale group decision-making with incomplete intuitionistic fuzzy preference relations," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 75(6), pages 1157-1177, June.
    4. Meimei Xia & Zeshui Xu & Na Chen, 2013. "Some Hesitant Fuzzy Aggregation Operators with Their Application in Group Decision Making," Group Decision and Negotiation, Springer, vol. 22(2), pages 259-279, March.
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