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Multi-Criteria Decision Making to Logarithmic Pythagorean Fuzzy Entropy Measure Under TOPSIS Approach

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  • H. D. Arora

    (Amity Institute of Applied Science, Amity University, Noida, India)

  • Anjali Naithani

    (Amity Institute of Applied Science, Amity University, Noida, India)

Abstract

One of the most essential ideas for tracing the best objects among a set of possible ones is decision-making theory. We make decisions to gain a wide range of advantages from them based on our previous experiences. The concept of Pythagorean fuzzy sets (PFS) was first established by Yager to provides a new technique to describe ambiguity with great precision when compared to intuitionistic fuzzy sets (IFS) and fuzzy sets (FS). The study of PFS is recently gaining importance due to its wide application in situations involving ambiguity. It can easily be merged with MADM techniques to solve real-life problems. However, many of these measures for PFS are ineffective in the sense that they have fundamental shortcomings that restrict them from providing reliable and consistent results. This paper provides a novel Pythagorean fuzzy entropy measure and its application to decision-making problem using technique for order preference by similarity of ideal solution (TOPSIS) on some real-life environment. Comparative study is also done for validation of the proposed measure.

Suggested Citation

  • H. D. Arora & Anjali Naithani, 2022. "Multi-Criteria Decision Making to Logarithmic Pythagorean Fuzzy Entropy Measure Under TOPSIS Approach," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 11(4), pages 1-23, October.
    • Handle: RePEc:igg:jfsa00:v:11:y:2022:i:4:p:1-23
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