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A Consensus Model for Large-Scale Group Decision-Making Based on the Trust Relationship Considering Leadership Behaviors and Non-cooperative Behaviors

机译:考虑领导行为和非合作行为的信任关系基于信任关系的大规模集团决策的共识模型

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摘要

Large-scale group decision-making (LSGDM) based on social networks has become an important part of practical decision-making. The trust relationship in social networks has an influence on not only the clustering process but also the consensus reaching process (CRP). Decision-makers (DMs) can take different behaviors by using the trust relationship to influence consensus reaching, so identifying the adjustment behaviors of DMs in CRP is essential. This study considers the influence of the trust relationship on the CRP and proposes a behavior analysis-based consensus model that comprehensively considers the leadership behaviors and non-cooperative behaviors. First, based on the clustering result, the preference similarity of two DMs with the direct trust relationship is calculated to judge whether leadership behavior exists. By judging the leadership behaviors, the number of effective DMs involved in LSGDM will be reduced. Second, based on the identification of leadership behaviors, the non-cooperative or cooperative behaviors are defined by judging whether the adjustment behaviors of effective DMs are conducive to achieving group consensus. Third, the weights of effective DMs and subgroups are punished or rewarded by quantifying the degree of non-cooperative or cooperative behaviors. Finally, the simulation experiments and comparative analysis are presented to illustrate the efficiency of the proposed method.
机译:基于社交网络的大规模集团决策(LSGDM)已成为实际决策的重要组成部分。社交网络中的信任关系不仅影响了聚类过程,还具有相互达成过程(CRP)的影响。决策者(DMS)可以采用不同的行为来使用信任关系来影响共识到达,因此识别CRP中DMS的调整行为至关重要。本研究考虑了信任关系对CRP的影响,并提出了一种以行为分析的共识模型,全面考虑领导行为和非合作行为。首先,基于聚类结果,计算两个DMS与直接信任关系的偏好相似度,以判断是否存在领导行为。通过判断领导行为,将减少LSGDM中涉及的有效DMS的数量。其次,根据领导行为的识别,通过判断有效DMS的调整行为是否有利于实现组共识来定义非合作或合作行为。第三,通过量化非合作或合作行为的程度来惩罚或奖励有效DMS和亚组的重量。最后,提出了模拟实验和比较分析以说明所提出的方法的效率。

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