International Data Science & Engineering Symposium

Supplier Selection Using an Intuitionistic Fuzzy Evaluation System

Ayşenur AKIN M. Bahar BAŞKIR Hamza GAMGAM

Abstract

Selection and evaluation problems have uncertainties due to concept and its perception discrepancies. Fuzzy set theory is one of the widely used methodology to cope with these uncertainties. There is a growing interest in evaluations using intuitionistic fuzzy sets. Differently from fuzzy sets, intuitionistic sets include both belonging degrees and nonbelonging degrees. Thus, the evaluation using intuitionistic fuzzy sets gives more realistic results. In this study, an intuitionistic fuzzy set-based evaluation system is proposed for supplier selection problem of a construction company. This system has qualitative- and quantitative evaluation parts. As qualitative part, decision makers of the company evaluate suppliers by the supplier selection criteria: i) quality, ii) price, iii) delivery, iv) productivity, v) service, vi) flexibility. The quantitative part includes supplier scores calculated through the current evaluation system of the company. A supplier-evaluation database was created by the abovementioned parts. The database was structured by α-cut representation of the evaluations. The calculations using intuitionistic fuzzy sets were done for this database, which was occurred by lower and upper bounds. After defuzzifying the database, suppliers were classified using the well-known fuzzy clustering algorithm, fuzzy c-means. The classification using fuzzy clustering algorithm has 95.0% accuracy.



Conference
International Data Science & Engineering Symposium
Keywords
Intuitionistic Fuzzy Sets Supplier Selection Fuzzy Clustering α-Cuts Accuracy

Language
English

Subject
Engineering

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