Malaya Journal of Matematik, Vol. 8, No. 1, 230-234, 2020 https://doi.org/10.26637/MJM0801/0039 A new integrated approach of combined FCM and CODAS method in interval valued intuitionistic fuzzy cognitive map for multi criteria decision making to evaluate and prioritize the branded mobile phones L. Arockia Angeline 1 , A. Rosa Mystica 2 , S. Fabiana Jacintha Mary 3 , M. Mary Mejrullo Merlin 4 * Abstract In highly complex linear problems dealing with uncertainty, FCM are used to aid decision making. In multi criteria decision making (MCDM), intuitionistic fuzzy sets have been employed whereas interval valued intuitionistic fuzzy cognitive Maps are used in business decision making because of the increasing complexity of business environment. But IFS are mainly employed in MCDM. A new MCDM technique called combinative distance based assessment (CODAS) helps us to choose the alternative having the largest Euclidean and hamming distances from the negative ideal point. In this paper, a new integrated approach of combined FCM and multi criteria decision making -CODAS with IVIFCM. In order to find the effectiveness of the developed model, it is applied in the consumers perception of choice towards the selection of branded mobile phones. Keywords Intuitionistic Fuzzy Cognitive Map, Ranking method (CODAS), Weighted vector, Mobile phone selection. AMS Subject Classification 03B52. 1,2,3,4 PG & Research Department of Mathematics, Holy Cross [Affiliated to Bharathidasan University, Tiruchirappalli-620024, Tamil Nadu, India.], Trichy-620002, Tamil Nadu, India. *Corresponding author: 2 mery24370@gmail.com Article History: Received 25 November 2019; Accepted 18 February 2020 c 2020 MJM. Contents 1 Introduction ....................................... 230 2 Preliminaries ...................................... 231 3 Conclusion ........................................ 234 References ........................................ 234 1. Introduction In FCM, fuzzy weights are given for causal relationships as w ij . These are used to assess the edge from concept j to concept i. In FCM’s, the concepts j and i in FCMs are connected by edges to represent the positive and negative relationships between the concepts [5]. An FCM is a fuzzy directed graph whose nodes represent fuzzy concepts within an application domain that occur to certain degree. Causal relations between the concepts are represented by directed edges. The strength of the relation between two concepts is weighted by the real values from E ∈ [−1, 1] [6]. For modeling and simulation of dynamic systems, FCMs are powerful tools, based on domain basic knowledge and experience. In FCM, concepts can be causally interrelated and through fuzzy logic uncertain and imprecise knowledge is represented. It represents a number of advantages over conventional fuzzy approaches to reasoning namely handling of conflicting infor- mation, easy construction and parameterization and mental models are compared rapidly with reality. In real life situations, many problems are encountered in decision making. In order to help the DMs elaborated suitable decisions, to rank alternative decision MCDM is found [4]. IFS are gene [6]. Realized fuzzy sets, in which their elements are charac- terized by both membership and non-membership value. The membership value indicates how much the degree to which an element belongs to the set whereas the non-membership value indicates to which degree it does not belong to the set.