Abstract

This paper mainly focuses on the consensus problems under fuzzy environment, in which experts’ original opinions take the form of intuitionistic fuzzy numbers. Based on the objective of minimizing the total consensus cost, we develop a novel intuitionistic minimum-cost consensus model (MCCM) in order to evaluate the deviation between individual opinions and group opinion. The proposed model can not only yield optimal adjusted individual opinions and consensus opinion, but also can explore index of each expert’s risk-bearing attitude. Additionally, some intuitionistic consensus models under WA operator and OWA operators are presented. With the help of multi-objective programming theory, linear-programming-based approaches are put forward to solve these consensus models. Finally, a numerical example is implemented to demonstrate the accuracy and effectiveness of the proposed models.

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