An Intelligent Approach for Multi-criterial Decision Making Using Similarity of Intuitionistic Fuzzy Sets

Abstract

We are living in the digital era with many modern technologies assisting people’s lives. However, making decisions with massive information still very difficult. In Multi-criterial decision-making (MCDM) problems, the information is usually uncertain and ambiguous. In such problems, applying fuzzy set seems to be appropriate but limited in information representation. The entropy based on similarity measures of intuitionistic fuzzy sets (IFS) can be applied to tackle such issues. In this work, we introduce a formula which can satisfy all the conditions of entropy. We also propose an algorithm applying a new entropy and similarity measures for portfolio selection problems. We demonstrate the proposed approach to rank assets in stock markets in Vietnam. The experimental results on the Vietnamese stocks data set show that our approach is very useful. The entropy and the similarity measures of IFS can be an alternative tool for solving portfolio selection problems.