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Consensus mechanism with maximum-return modifications and minimum-cost feedback: A perspective of game theory

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  • Zhang, Bowen
  • Dong, Yucheng
  • Zhang, Hengjie
  • Pedrycz, Witold

Abstract

In group decision making, the interaction behaviors between the moderator and decision makers play a critical role in a consensus process. In this study, based on the essential architecture of Stackelberg game, we present a bi-level optimization model to describe the interaction behaviors between decision makers and moderator, and develop the consensus mechanism with maximum-return modifications and minimum-cost feedback (MRMCCM). In the MRMCCM, the moderator aims to guide decision makers to reach consensus with minimum cost, while decision makers modify their own opinions based on the maximization of individual return. We analyze the equilibrium strategy in the MRMCCM, including the modification and compensation strategies composed of the optimal suggested opinion and unit consensus cost. In addition, an adaptive differential evolution is presented to deal with the bi-level optimization model, and the detailed experimental studies are conducted to justify the performance of the MRMCCM.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:287:y:2020:i:2:p:546-559
    DOI: 10.1016/j.ejor.2020.04.014
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    References listed on IDEAS

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    Cited by:

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    3. Meng, Fan-Yong & Gong, Zai-Wu & Pedrycz, Witold & Chu, Jun-Fei, 2023. "Selfish-dilemma consensus analysis for group decision making in the perspective of cooperative game theory," European Journal of Operational Research, Elsevier, vol. 308(1), pages 290-305.
    4. Du, Junliang & Liu, Sifeng & Liu, Yong, 2022. "A limited cost consensus approach with fairness concern and its application," European Journal of Operational Research, Elsevier, vol. 298(1), pages 261-275.
    5. Rodríguez, Rosa M. & Labella, Álvaro & Nuñez-Cacho, Pedro & Molina-Moreno, Valentin & Martínez, Luis, 2022. "A comprehensive minimum cost consensus model for large scale group decision making for circular economy measurement," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    6. Guo, Weiwei & Gong, Zaiwu & Zhang, Wei-Guo & Xu, Yanxin, 2023. "Minimum cost consensus modeling under dynamic feedback regulation mechanism considering consensus principle and tolerance level," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1279-1295.
    7. Gong, Zaiwu & Guo, Weiwei & Słowiński, Roman, 2021. "Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction," Omega, Elsevier, vol. 104(C).
    8. Li, Yanhong & Kou, Gang & Li, Guangxu & Peng, Yi, 2022. "Consensus reaching process in large-scale group decision making based on bounded confidence and social network," European Journal of Operational Research, Elsevier, vol. 303(2), pages 790-802.
    9. Liang, Decui & Fu, Yuanyuan & Ishizaka, Alessio, 2023. "A consensual group ELECTRE-SORT approach considering the incomparable classes with the application of machine maintenance strategy assignment," Omega, Elsevier, vol. 118(C).
    10. Ying Ji & Huanhuan Li & Huijie Zhang, 2022. "Risk-Averse Two-Stage Stochastic Minimum Cost Consensus Models with Asymmetric Adjustment Cost," Group Decision and Negotiation, Springer, vol. 31(2), pages 261-291, April.
    11. Li, Ying & Liu, Peide & Li, Gang, 2023. "An asymmetric cost consensus based failure mode and effect analysis method with personalized risk attitude information," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

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