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An Adaptive Core-Nash Bargaining Game Consensus Mechanism for Group Decision Making

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Listed:
  • Jie Tang

    (Nanjing University of Information Science and Technology)

  • Fanyong Meng

    (Central South University)

Abstract

As a process for ensuring the agreeable degree of individual opinions, consensus analysis is crucial for GDM. This paper focuses on the adaptive consensus mechanism. That's, different adjustment strategies are employed for various consensus levels. Unlike the feedback iteration method, this paper introduces an optimization model-based consensus-reaching procedure. To do this, optimal models are built to determine the minimum consensus adjustment at different levels. Then, the individual minimum consensus adjustment is analyzed, and the inconsistency between individual and group minimum consensus adjustments is concluded. After that, consensus adjustment cooperative games at three levels are proposed to allocate the total minimum consensus adjustment in view of the comprehensive evaluation. We can obtain the coalitional stability allocation scheme using the core of constructed cooperative games. Additionally, core-Nash bargaining games at three levels are proposed to ensure the fairness and coalitional stability of allocation results. Finally, a numerical example is offered to indicate the application of the new theoretical developments.

Suggested Citation

  • Jie Tang & Fanyong Meng, 2024. "An Adaptive Core-Nash Bargaining Game Consensus Mechanism for Group Decision Making," Group Decision and Negotiation, Springer, vol. 33(4), pages 805-837, August.
    • Handle: RePEc:spr:grdene:v:33:y:2024:i:4:d:10.1007_s10726-024-09888-8
    DOI: 10.1007/s10726-024-09888-8
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    References listed on IDEAS

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    1. Xunjie Gou & Zeshui Xu & Xinxin Wang & Huchang Liao, 2021. "Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making," Fuzzy Optimization and Decision Making, Springer, vol. 20(1), pages 51-79, March.
    2. Lloyd S. Shapley, 1967. "On balanced sets and cores," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 14(4), pages 453-460.
    3. Tang, Ming & Liao, Huchang & Xu, Jiuping & Streimikiene, Dalia & Zheng, Xiaosong, 2020. "Adaptive consensus reaching process with hybrid strategies for large-scale group decision making," European Journal of Operational Research, Elsevier, vol. 282(3), pages 957-971.
    4. Zhang, Bowen & Dong, Yucheng & Zhang, Hengjie & Pedrycz, Witold, 2020. "Consensus mechanism with maximum-return modifications and minimum-cost feedback: A perspective of game theory," European Journal of Operational Research, Elsevier, vol. 287(2), pages 546-559.
    5. Tang, Ming & Liao, Huchang & Mi, Xiaomei & Lev, Benjamin & Pedrycz, Witold, 2021. "A hierarchical consensus reaching process for group decision making with noncooperative behaviors," European Journal of Operational Research, Elsevier, vol. 293(2), pages 632-642.
    6. Dong, Yucheng & Xu, Yinfeng & Li, Hongyi & Feng, Bo, 2010. "The OWA-based consensus operator under linguistic representation models using position indexes," European Journal of Operational Research, Elsevier, vol. 203(2), pages 455-463, June.
    7. Okada, Akira, 2010. "The Nash bargaining solution in general n-person cooperative games," Journal of Economic Theory, Elsevier, vol. 145(6), pages 2356-2379, November.
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