Two new optimal aggregation approaches of fuzzy opinions in group decision environment

The aggregation of fuzzy opinions is an important component of group decision analysis with fuzzy information. This paper proposes two new approaches for the assessment of the weights to be associated with fuzzy opinions. These approaches involve, respectively, the minimization of the sum of squared differences between the individual weighted fuzzy opinion and the weighted mean value of all fuzzy opinions, which is called the weighted minimum variance method (WMVM), and the minimax differences between the possibilistic mean value of a weighted fuzzy opinion and the possibilistic mean value of the weighted mean value, which is called the possibilistic mean value minimax differences method (PMVMDM). The two approaches are developed and numerical examples are presented to illustrate their simplicity and effectiveness in aggregating fuzzy opinions.