Multiattribute decision making based on intuitionistic fuzzy interaction average operators: a comparison

This paper proposes a new family of intuitionistic fuzzy information aggregation operators for multiattribute decision making. Such aggregate operators provide an excellent complement to the existing ones. In this study, comparison with existing intuitionistic fuzzy aggregation operators is presented in detail. Properties and special cases of the proposed operators are investigated. Finally, we introduce an approach to intuitionistic fuzzy multiattribute decision making. An example of the recruitment of intern candidates is illustrated to show the feasibility and superiority of the proposed method.