Abstract
The Bonferroni mean (BM) was originally introduced by Bonferroni and then more recently generalized by Yager. The desirable characteristic of the BM is its capability to capture the interrelationship between input arguments. Nevertheless, it seems that the existing literature only considers the BM for aggregating crisp numbers instead of any other types of arguments. In this paper, we investigate the BM under intuitionistic fuzzy environments. We develop an intuitionistic fuzzy BM (IFBM) and discuss its variety of special cases. Then, we apply the weighted IFBM to multicriteria decision making. Some numerical examples are given to illustrate our results.
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