Diverse Ranking Approach in MCDM Based on Trapezoidal Intuitionistic Fuzzy Numbers

• Published in: Advances in Intelligent Systems and Computing
• Main Author: Tarmudi Z.; Abd Rahman N.
• Format: Conference paper
• Language: English
• Published: Springer Verlag 2020
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064918258&doi=10.1007%2f978-3-030-17065-3_2&partnerID=40&md5=9bff2e7853e3fd273a604f26bab10fd1

Intuitionistic fuzzy set (IFS) is a generalization of the fuzzy set that is characterized by the membership and non-membership function. It is proven that IFS improves the drawbacks in fuzzy set since it is designed to deal with the uncertainty aspects. In spite of this advantage, the selection of the ranking approach is still one of the fundamental issues in IFS operations. Thus, this paper intends to compare three ranking approaches of the trapezoidal intuitionistic fuzzy numbers (TrIFN). The ranking approaches involved are; expected value-based approach, centroid-based approach, and score function-based approach. To achieve the objective, one numerical example in prioritizing the alternatives using intuitionistic fuzzy multi-criteria decision making (IF-MCDM) are provided to illustrate the comparison of these ranking approaches. Based on the comparison, it was found that the alternatives MCDM problems can be ranked easily in efficient and accurate manner. © 2020, Springer Nature Switzerland AG.