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Design of Score Function for Decision Problem: with the Intuitionistic Fuzzy Sets Hesitation

Sanghyuk Lee, Kie-Hyuk Shin

Abstract


Hesitation analysis on the intuitionistic fuzzy sets (IFSs) has been carried out via hidden information and; negative and positive hesitation. Due to its casting vote role in decision, importance has been emphasized. Hesitation degree analysis is delivered from the mathematical definition, and the score function is designed based on the information overlap. Additionally, relation between fuzzy sets (FSs) and IFSs are also illustrated through figures, and each characteristic is also analyzed. Difference of FSs and IFSs are clear from the hesitation viewpoints, together with their similarity measure derivation. The obtained score function is applied to the example; multi-criteria decision problem. The proposed hesitation analysis provides more flexible and general results than FSs based score functions. In order to design score function, similarity measures are also considered by the existing results and our proposal. Classification results are illustrated in the examples, specifically dealing in purchasing product and decision making.

Keywords


Intuitionistic Fuzzy Sets; similarity measure; hesitation; membership degree; non-membership degree.

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