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Consensus reaching with non-cooperative behavior management for personalized individual semantics-based social network group decision making

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  • Yuan Gao
  • Zhen Zhang

Abstract

Leveraging social network trust relationships among experts to reach consensus has become a popular topic in linguistic group decision making (GDM). However, in linguistic contexts, it is commonly accepted that words mean different things for different people, which indicates the necessity of modeling experts’ personalized individual semantics (PISs). Moreover, experts sometimes may show non-cooperative behaviors during the consensus reaching process (CRP) due to their own interests. As a result, this paper focuses on developing a consensus reaching algorithm with non-cooperative behavior management for PIS-based social network GDM problems. First, linguistic preference relations are transformed into fuzzy preference relations by the PIS model, and then social network analysis techniques are used to obtain experts’ weight vector. Afterwards, we propose a feedback adjustment mechanism to improve experts’ adjustment willingness in CPRs, in which the trust relationships and the PISs of experts are utilized to generate adjustment advice for experts. Furthermore, a non-cooperative behavior management mechanism which dynamically adjusts the trust degrees in social network is devised. Followed by this, a numerical example is provided to demonstrate the proposed algorithm. Finally, detailed simulation results are presented to analyze the influence of different parameters on CRPs and illustrate the validity of the proposed algorithm.

Suggested Citation

  • Yuan Gao & Zhen Zhang, 2021. "Consensus reaching with non-cooperative behavior management for personalized individual semantics-based social network group decision making," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(11), pages 2518-2535, December.
    • Handle: RePEc:taf:tjorxx:v:73:y:2021:i:11:p:2518-2535
    DOI: 10.1080/01605682.2021.1997654
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    Cited by:

    1. Iraj Mohammadfam & Ali Asghar Khajevandi & Hesam Dehghani & Mohammad Babamiri & Maryam Farhadian, 2022. "Analysis of Factors Affecting Human Reliability in the Mining Process Design Using Fuzzy Delphi and DEMATEL Methods," Sustainability, MDPI, vol. 14(13), pages 1-19, July.
    2. Zhen Zhang & Zhuolin Li, 2023. "Consensus-based TOPSIS-Sort-B for multi-criteria sorting in the context of group decision-making," Annals of Operations Research, Springer, vol. 325(2), pages 911-938, June.
    3. Fang Xu & Mengfan Yan & Lun Wang & Shaojian Qu, 2022. "The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    4. Jiang, Jing & Liu, Xinwang & Wang, Weizhong & Deveci, Muhammet, 2023. "Assessing the impact of healthcare service risks on healthcare demand under evolving economic and social structures: An improved GLDS decision making method considering risk attitudes," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 459-479.

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