A new information fusion algorithm for handling heterogeneous group decision-making problems

We present an information fusion algorithm based on the similarity measure, the FN-IOWA operator, and the linguistic quantifiers for aggregating fuzzy opinions in a heterogeneous group decision-making environment. The proposed information fusion algorithm can handle the heterogeneous fuzzy group decision-making problems in a more flexible and more intelligent manner due to the fact that it not only uses generalized fuzzy numbers to represent fuzzy opinions and the degrees of confidence of the fuzzy opinions of the decision-makers, but also uses linguistic quantifiers to aggregate the decision-makers' fuzzy opinions for different linguistic constraints.