Social network group decision making with minimum cost and maximum satisfaction consensus based on bargaining game

In group decision making (GDM), different decision makers (DMs) will provide different evaluation opinions for alternatives. Consensus-reaching process on these opinions is a critical issue. To improve consensus efficiency, a dynamic social network GDM method based on a bargaining game is developed. First, we build a minimum total cost consensus model for the moderator and then a maximum individual satisfaction consensus model for inconsistent DMs. For the difference in the modified opinions and unit compensation derived from these two types of models, we devise offer-counteroffer strategies for the moderator and DMs under various cases. At the same time, we establish a complete management system for the DM weights based on different behaviors in consensus promotion. In addition, we formulate the trust evolution process of all types of DMs to further update the weights of DMs. Based on this, a consensus feedback iterative mechanism driven by the trust network is constructed. Finally, we use the example of location of an international R&D center to illustrate the entire GDM process. The comparative analysis demonstrates the effectiveness of the proposed method.