A Multi-Attribute Large Group Decision-Making Method Based on Fuzzy Preference Dynamic Information Interacting

Abstract

Given that the traditional fuzzy group decision-making model does not take the process of information interaction into consideration, this paper proposes a large group decision-making method which is based on fuzzy preference dynamic information interaction. This method adopts intuitionistic fuzzy sets (IFSs) to represent decision preference values, defines the similarity between two IFSs and calculates the similarity between the preference vectors of each expert and the ideal alternative. The average similarity of group and the decision deviations of experts are presented. If the decision deviation is greater than the given threshold, the experts are required to revise their decision preferences. Until the decision deviation of each expert is less than the given threshold, we come to the decision-making stage. The weighted similarity between each alternative and the ideal alternative is calculated, and then decision alternatives are ranked by sorting the weighted similarity. The optimal solution is selected according to the maximum principle. At last, an example is taken to simulate the implementation process and the result shows the feasibility and the validity of this method.