Defuzzification of Intuitionistic Z-Numbers for Fuzzy Multi Criteria Decision Making

• Published in: Lecture Notes in Networks and Systems
• Main Author: Nik Badrul Alam N.M.F.H.; Ku Khalif K.M.N.; Jaini N.I.; Abu Bakar A.S.; Abdullah L.
• Format: Conference paper
• Language: English
• Published: Springer Science and Business Media Deutschland GmbH 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115210435&doi=10.1007%2f978-3-030-85577-2_101&partnerID=40&md5=cf319757f79a661a8c4fde587a117ac0

Z-numbers and intuitionistic fuzzy numbers are both important as they consider the reliability of the judgement, membership and non-membership functions of the numbers. The combination of these two numbers produce intuitionistic Z-numbers which need to be defuzzified before aggregation of multiple experts’ opinions could be done in the decision making problems. This paper presents the generalised intuitionistic Z-numbers and proposes a centroid-based defuzzification of such numbers, namely intuitive multiple centroid. The proposed defuzzification is used in the decision making model and applied to the supplier selection problem. The ranking of supplier alternatives is evaluated using the ranking function based on centroid. In the present paper, the ranking is improved since the intuitionistic fuzzy numbers (IFN) are integrated within the evaluations which were initially in form of Z-numbers, considering their membership and non-membership grades. The ranking of the proposed model gives almost similar ranking to the existing model, with simplified but detailed defuzzification method. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.