A New Similarity Measure of Intuitionistic Fuzzy Multi Sets in Medical Diagnosis Application N. Uma Department of Mathematics, Sri Ramakrishna College of Arts and Science (Formerly SNR Sons College), Coimbatore, Tamil Nadu. (INDIA). umasnr@gmail.com ABSTRACT As Similarity Measure is an important topic in fuzzy set theory, the objective of this paper is to introduce a new efficient Similarity measure for Intuitionistic fuzzy multi sets (IFMS). This method considers multi membership, non-membership and hesitancy degree for the same element. This novel Similarity measure for IFMS is the combination of MAX / MIN operators of the membership functions and the Zhang and Fu’s measure of the IFMS. We apply this appreciable measure to medical diagnosis as it satisfies all the properties of the Similarity Measure. KEY WORDS: Intuitionistic fuzzy set, Fuzzy Multi sets, Intuitionistic Fuzzy Multi sets, Similarity measure, Max and Min operators. I. INTRODUCTION The Intuitionistic Fuzzy sets (IFS) proposed by Krasssimir T. Atanassov[1, 2] was the generalisation of the Fuzzy set (FS) introduced by Lofti A. Zadeh [3]. The object, partially belong to a set with a membership degree ( ) between 0 and 1 are represented by the FS whereas the IFS represent the uncertainty with respect to both membership ( ) and non-membership ( ) such that . Here, the number is the hesitation degree or intuitionistic index ( . International Journal of Pure and Applied Mathematics Volume 119 No. 17 2018, 859-872 ISSN: 1314-3395 (on-line version) url: http://www.acadpubl.eu/hub/ Special Issue http://www.acadpubl.eu/hub/ 859