A C-OWA Operator-based Method for Aggregating Intuitionistic Fuzzy Information and Its Application to Decision Making under Uncertainty

Abstract An IFS is suitable way to deal with uncertainty, but operators on it are complex in computation even though they work well. This study presents a C-OWA operator-based method to make aggregation over intuitionistic fuzzy information more easy and convenient, and then applies it to complicated decision making under uncertainty. IFNs or IIFNs are transformed into intervals which are easy to be aggregated to real values according to the risk preference of decision makers by C-OWA operator. In this way an uncertain decision problem might be converted into a certain one which is much easier to solve. Experimental study examines the feasibility and validity of the presented method.