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<p>In group decision making (<i>GDM</i>) problems, fuzzy social networks (<i>FSNs</i>) provide a new theoretical framework for trust management among decision makers (<i>DMs</i>) and play a key role in weight allocation, opinion dissemination, and consensus building. However, the problem of trust risk still cannot be ignored. To this end, this study proposes an innovative <i>GDM</i> optimization method, <i>TWD-FSN-A-PT</i>, from the perspectives of optimization computation and decision-making application. The method combines the theory of three-way decision (<i>TWD</i>) theory and <i>FSN</i>s, aiming at solving the problem of trust risk and behavioral tendency in fuzzy environments. Specifically, the innovations of the method include: identifying and reducing pseudo-trust risk using the <i>TWD</i> theory; adopting a new mechanism to distinguish between selfish and altruistic behaviors of <i>DMs</i> by considering both group and individual optimization; and maximizing global stability by optimizing the model and respecting individual preferences, which ensures that the adjustment cost is minimized while reaching an efficient consensus. These innovative methods fully rely on the theory and techniques of applied mathematics and ensure the robustness of the model under different parameter settings. Finally, the <i>TWD-FSN-A-PT</i> method is applied to the regional electricity demand analysis, demonstrating the results of ranking the electricity demand at different time periods.</p>

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Group consensus optimization based on fuzzy social networks for pseudo-trust recognition from a three-way decision perspective

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Xinru Han,
  • Yukun Bao,
  • Jianming Zhan,
  • Liang Shen

摘要

In group decision making (GDM) problems, fuzzy social networks (FSNs) provide a new theoretical framework for trust management among decision makers (DMs) and play a key role in weight allocation, opinion dissemination, and consensus building. However, the problem of trust risk still cannot be ignored. To this end, this study proposes an innovative GDM optimization method, TWD-FSN-A-PT, from the perspectives of optimization computation and decision-making application. The method combines the theory of three-way decision (TWD) theory and FSNs, aiming at solving the problem of trust risk and behavioral tendency in fuzzy environments. Specifically, the innovations of the method include: identifying and reducing pseudo-trust risk using the TWD theory; adopting a new mechanism to distinguish between selfish and altruistic behaviors of DMs by considering both group and individual optimization; and maximizing global stability by optimizing the model and respecting individual preferences, which ensures that the adjustment cost is minimized while reaching an efficient consensus. These innovative methods fully rely on the theory and techniques of applied mathematics and ensure the robustness of the model under different parameter settings. Finally, the TWD-FSN-A-PT method is applied to the regional electricity demand analysis, demonstrating the results of ranking the electricity demand at different time periods.