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Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method

Author

Listed:
  • Wenqi Liu

    (Dongbei University of Finance and Economics)

  • Hengjie Zhang

    (Hohai University)

  • Haiming Liang

    (Sichuan University)

  • Cong-cong Li

    (Southwest Jiaotong University)

  • Yucheng Dong

    (Sichuan University
    Shenzhen Institute of Information Technology)

Abstract

Preference relations are one of the most common tools used to represent decision makers’ preferences. Self-confident preference relations, whose preference elements include self-confidence levels and preference values, is a new and effective tool that can be used to express decision makers’ self-confidence levels in the preference relation. When using self-confident preference relations in group decision-making problems, the individual consistency and group consensus are two fundamental issues. To deal with these issues, a consistency index is proposed to measure the consistency level of a self-confident additive preference relation. Meanwhile, a consensus index is presented to measure the group consensus level of self-confident additive preference relations. Subsequently, two nonlinear optimization methods are developed to manage consistency and consensus issues for group decision-making within the context of consensus reaching without feedback. The first model is used to derive self-confident additive preference relations with acceptable consistency, and the second optimization model is employed to promote consensus reaching that simultaneously manage individual consistency. A hypothetical application with comparative analysis is conducted to show the usability and validity of the proposed methods.

Suggested Citation

  • Wenqi Liu & Hengjie Zhang & Haiming Liang & Cong-cong Li & Yucheng Dong, 2022. "Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method," Group Decision and Negotiation, Springer, vol. 31(1), pages 213-240, February.
    • Handle: RePEc:spr:grdene:v:31:y:2022:i:1:d:10.1007_s10726-021-09766-7
    DOI: 10.1007/s10726-021-09766-7
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    References listed on IDEAS

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    1. Tiantian Gai & Mingshuo Cao & Francisco Chiclana & Zhen Zhang & Yucheng Dong & Enrique Herrera-Viedma & Jian Wu, 2023. "Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making," Group Decision and Negotiation, Springer, vol. 32(1), pages 45-74, February.

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