Parametric (R,S)-norm Entropy on Intuitionistic Fuzzy Sets with a New Approach in Multiple Attribute Decision Making

Abstract

The theory of intuitionistic fuzzy sets (IFSs) is well suitable to deal with vagueness and hesitancy. In the present communication, a new parametric (R,S)-norm intuitionistic fuzzy entropy is proposed with the proof of validity and some of its properties also discussed. The intuitionistic fuzzy entropy is useful to represent the decision information in decision making process since it is characterized by the degree of satisfiability, degree of non-satisfiability and hesitancy degree. Based on this proposed IF entropy, a new multiple attribute decision making (MADM) method is introduced and compared with an existing method. In case of attributes weight, two cases (one with completely unknown attributes weight and other with partially known attributes weight) are discussed with the help of examples. In the end, a case study of insurance companies on the basis of service qualitities is given.

Keywords

• Intuitionistic fuzzy entropy
• (R,S)-norm intuitionistic fuzzy entropy
• Multiple attribute decision making
• TOPSIS
• Weighted hamming distance