A Dissonance Reduction Method for Intuitionistic Fuzzy Multi-Criteria Decision-Making Problems

Considering that cognitive dissonance is regarded as a momentous psychological factor in the decision making, this study proposes new techniques not only to tackle multi-criteria decision making problems but also to reduce the cognitive dissonance yielded by the decision maker under intuitionistic fuzzy environment. By applying the intuitionistic fuzzy weighted averaging (IFWA) operator and the score function, the proposed method derives the optimal weights of criteria and generates the priority of alternatives from the mathematical programming. In order to diminish the dissonance, the attractiveness of alternatives is magnified as large as possible in the programming problem based on the Euclidean distance. A numerical example is given to demonstrate the detailed calculating procedure; besides, an empirical case concerning a digital camera selection problem is employed to ascertain the feasibility of the developed method. According to the empirical results, the optimal alternative calculated by the mathematical programming satisfies decision makers and indeed reduces the dissonance. This study comes up with a successful manner to effectively reduce the dissonance when decision makers face a multi-criteria decision making problem.