Prioritized Fuzzy Information Fusion for Handling Multi-Criteria Fuzzy Decision-Making Problems

Abstract

The prioritized operator is very useful in dealing with multi–criteria fuzzy decision-making problems, and it can be seen as an additional selector of filter. In this article, we present a prioritized information fusion algorithm based on similarity measures of generalized fuzzy numbers for aggregating fuzzy information. The proposed information fusion algorithm can handle multi–criteria fuzzy decision–making problems in a more flexible manner due to the fact that it allows the evaluating values of the criteria to be represented by crisp values between [0, 1] or generalized fuzzy numbers, where the generalized fuzzy numbers can indicate the degrees of confidence of the decision-makers’ opinions.