Intuitionistic fuzzy exponential divergence: Application in multi-attribute decision making

The aim of this paper is to introduce an exponential methodology for measuring the degree of divergence between two intuitionistic fuzzy sets. For this, an intuitionistic fuzzy exponential divergence measure is proposed and its important properties are discussed axiomatically. In addition, the applicability and efficiency of the proposed intuitionistic fuzzy exponential divergence measure have been demonstrated by comparing with existing intuitionistic fuzzy divergence measures using a numerical example in the framework of pattern recognition. Further, a method to solve multi-attribute decision making problem using the proposed divergence measure in intuitionistic fuzzy environment is presented with an illustrative example. Lastly, a comparative study of the proposed method with the existing TOPSIS and MOORA methods of multi-attribute decision making in an intuitionistic fuzzy environment is presented.