Supplier selection using a novel intuitionist fuzzy clustering approach

Supplier selection is a complicated decision-making problem involving multicriteria, alternative and decision makers (DMs). The main purpose of this paper is to demonstrate the use of a clustering-based method to solve a group decision making (GDM) problem and, also to achieve more realistic and homogeneous results. Intuitionistic fuzzy value (IFV) is used to show the decision makers’ preferences and IFN clustering method is utilized to cluster around DM's preferences. Intuitionistic fuzzy weighted geometric (IFWG) is applied to aggregate the obtained clusters. Ranking process is used based on the two indices, score function and accuracy function, to rank the alternatives. Lastly, to demonstrate the efficiency of our proposed method, it is implemented to choose suppliers in a car factory.The strength of the propose approach is considering the group agreement on proposed DMs’ preferences for giving different effect on their judgment. Besides, encountering the qualitative judgment of DMs using IFV concept with score function and the accuracy function for modeling the DMs’ knowledge is the other contribution of this paper.

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► We proposed a supplier selection method using a novel intuitionist fuzzy clustering approach.
► We used a clustering-based method to solve a group decision making problem.
► IFN clustering method is utilized to cluster around DM's preferences.
► IFWG is used to aggregate the clusters.
► Ranking process is utilized based on score and accuracy function.