A Fuzzy TOPSIS Decision Making Model with Entropy Weight under Intuitionistic Fuzzy Environment

The theory of intuitionistic fuzzy set (IFS) is well suitable to deal with vagueness and hesitancy. In this study, we propose a new fuzzy TOPSIS decision making model using entropy weight for dealing with multiple criteria decision making (MCDM) problems under intuitionistic fuzzy environment. This model allows measuring the degree of satisfiability and the degree of non-satisfiability, respectively, of each alternative evaluated across a set of criteria. To obtain the weighted fuzzy decision matrix, we employ the concept of Shannon's entropy to calculate the criteria weights. An investment example is used to illustrate the application of the proposed model. Index Terms—Entropy, Intuitionistic fuzzy set (IFS), Multiple criteria decision making (MCDM), TOPSIS I. INTRODUCTION A lot of multiple criteria decision making (MCDM) approaches have been developed and applied to diverse fields, like engineering, management, economics, etc. As one of the known classical MCDM approaches, TOPSIS (technique for order performance by similarity to ideal solution) was first developed by Hwang and Yoon (6). The primary concept of