Novel Pythagorean Fuzzy Entropy with Application in MCDM to assess the Best Automotive Company

The fuzzy sets are quite proficient to handle inconsistency, vagueness, and improper information in many theoretical and practical problems in the multicriteria decision procedures. The Pythagorean fuzzy set (PFS) is significantly used in many complex problems in multicriteria decision making as compared to (IFS) intuitionistic fuzzy set. Moreover, The PFS are enabled to handle the fuzziness more precisely. In this context, this communication presents the novel entropy on PFS. The result of the new entropy measure has been validated for upon the ranking of the best automotive company-based technique for order preference by similarity to ideal solution (TOPSIS) model with (MCDM) multicriteria decision making. The comparative analysis of results with existing entropy measures defined on PFS concludes that novel entropy measure is more reliable, feasible, and precise.