A Consensus Model for Intuitionistic Fuzzy Group Decision-Making Problems Based on the Construction and Propagation of Trust/Distrust Relationships in Social Networks

The preference values in group decision-making (GDM) process can differ significantly between different experts, which may yield a low level of group consensus. Therefore, different consensus models have been developed for the modification of preference values to assist experts in improving their consensus degrees. However, most consensus models do not consider collective intelligence (CI) that may decrease as the consensus degree increases under certain circumstances. From the perspective of CI, the distrust relationship allows the group to better explore the decision space, rather than prematurely converge on an agreed suboptimal solution. Inspired by this idea, a theoretical framework of solving intuitionistic fuzzy GDM problems with low group consensus is proposed in this paper, which mainly includes two steps: (1) building the trust/distrust relationships and (2) establishing a consensus model. For two experts with a direct relationship, the trust/distrust relationships between them are constructed by fusing their knowledge levels and representativeness levels. For two experts with an indirect relationship, a new operator is designed to construct the trust/distrust relationships between them, which can describe the information attenuation of the decreasing trust along with the increasing distrust. Additionally, a consensus model based on the social network relationships density and trust/distrust relationships is proposed, which improves consensus degree and CI level conducively. Finally, a ranking of alternatives is constructed to select the optimal alternative. An illustrative example is used to demonstrate the effectiveness and applicability of the proposed method.