Research And Application Of Group Decision Consensus Model Based On Trust Network

Consensus feedback mechanism is a key link in group decision making activities for decision makers to form a consensus opinion on alternatives.With the progress of society,it will be more and more difficult to form a consensus opinion in increasingly complex decision-making scenarios,and it is necessary to study the feedback mechanism in the consensus process in depth.In recent years,the widespread popularity of social media has accelerated the interaction and information transfer among decision makers,making the changes in the relationship between decision makers with network characteristics,which provides a new research perspective for the development of group consensus mechanism.The information of social relations among decision makers often changes dynamically with the consensus reaching process,which in turn can affect the changes of decision outcomes.Therefore,it is important to analyze the characteristics of group relationship changes in social networks and construct the group consensus reaching mechanism under social networks.In addition,group consensus reaching is a dynamic interactive process in which multiple factors interact with each other,and existing studies have ignored the connection between social relationships,decision-making behaviors and perspectives among decision makers in group decision making.Based on this,this paper focuses on the theory and method of group decision making to explore the interrelationship among decision makers’ viewpoint behavior,viewpoint and trust based on the perspective of social network,and analyze the influence of social network structure on the efficiency of group consensus reaching and decision outcome.The main research work of this paper is as follows.(1)A hybrid dynamic trust network among decision makers is constructed.In the process of hybrid dynamic trust network construction,this study proposes an algorithm to calculate the importance of network nodes,which mainly adopts the centrality analysis of social networks to synthesize and obtain the importance of network nodes,and applies it to the trust propagation and aggregation process.Based on the concept of bounded confidence,the historical static trust relationship based on the social relationship of decision makers and the temporary dynamic trust relationship based on the similarity of views are fused to build a hybrid dynamic trust network among decision makers,which can truly reflect the evolution of trust relationship among decision makers in the process of group consensus reaching.(2)An extended bounded confidence-based group consensus feedback mechanism is designed.In the proposed extended bounded confidence model,based on social identity theory,a trust reward and punishment factor is introduced to obtain the evolution trend of trust relationship among decision makers,and the bounded confidence set of decision makers is extended.The applicability and scientific validity of the proposed mechanism are verified through relevant plant site selection calculations and comparative studies.(3)A two-path cluster consensus feedback mechanism based on adaptive transformation of decision makers’ behavior is designed.This study argues that there is an adaptive shift in decision behavior in the process of group consensus reaching.Therefore,a decision behavior-driven group consensus reaching mechanism,i.e.,a dual-path feedback mechanism based on adaptive transformation of dynamic hybrid trust network,is proposed.In the designed feedback mechanism,decision makers who do not satisfy the group consensus requirements are identified,and suggestions for opinion or weight modification are provided to the decision makers based on their self-confidence degree(SCD)and average trust in others(AD-TIO).The effectiveness and flexibility of the proposed mechanism are verified through joint investment decision arithmetic,relevant sensitivity analysis,and comparative studies.