Diverse Ranking Approach in MCDM Based on Trapezoidal Intuitionistic Fuzzy Numbers

  • Zamali TarmudiEmail author
  • Norzanah Abd Rahman
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 942)


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.


Intuitionistic fuzzy set Trapezoidal intuitionistic fuzzy numbers Multi-criteria decision-making Ranking approach 



This research was supported by grant of Fundamental Research Grant Scheme (FRGS) from Ministry of Education (formerly known as Ministry of Higher Education (MOHE) Malaysia and Universiti Teknologi MARA (UiTM), Malaysia, reference no.: 600-IRMI/FRGS 5/3(84/2016).


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Authors and Affiliations

  1. 1.Faculty of Computer and Mathematical SciencesUniversiti Teknologi MARA (Johor Branch)SegamatMalaysia
  2. 2.Faculty of Computer and Mathematical SciencesUniversiti Teknologi MARA (Sabah Branch)Kota KinabaluMalaysia

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