Intuitive multiple centroid defuzzification of intuitionistic Z-numbers

• Published in: Journal of fuzzy extension & applications (Online) Vol. 3; no. 2; pp. 126 - 139
• Main Authors: Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, Nor Izzati Jaini, Ahmad Syafadhli Abu Bakar, Lazim Abdullah
• Format: Journal Article
• Language: English
• Published: Ayandegan Institute of Higher Education 01.06.2022
• Subjects: defuzzification; intuitionistic z-numbers; intuitive multiple centroid; ranking function
• ISSN: 2783-1442; 2717-3453
• DOI: 10.22105/jfea.2022.315297.1173

In fuzzy decision-making, incomplete information always leads to uncertain and partially reliable judgements. The emergence of fuzzy set theory helps decision-makers in handling uncertainty and vagueness when making judgements. Intuitionistic Fuzzy Numbers (IFN) measure the degree of uncertainty better than classical fuzzy numbers, while Z-numbers help to highlight the reliability of the judgements. Combining these two fuzzy numbers produces Intuitionistic Z-Numbers (IZN). Both restriction and reliability components are characterized by the membership and non-membership functions, exhibiting a degree of uncertainties that arise due to the lack of information when decision-makers are making preferences. Decision information in the form of IZN needs to be defuzzified during the decision-making process before the final preferences can be determined. This paper proposes an Intuitive Multiple Centroid (IMC) defuzzification of IZN. A novel Multi-Criteria Decision-Making (MCDM) model based on IZN is developed. The proposed MCDM model is implemented in a supplier selection problem for an automobile manufacturing company. An arithmetic averaging operator is used to aggregate the preferences of all decision-makers, and a ranking function based on centroid is used to rank the alternatives. The IZN play the role of representing the uncertainty of decision-makers, which finally determine the ranking of alternatives.