International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 6, No. 5, 8 Apr. 2014
Cover page and Table of Contents: PDF (size: 581KB)
Supplier Segmentation using Fuzzy Linguistic Preference Relations and Fuzzy Clustering
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Author(s)
Index Terms
Supply Chain Management (SCM), Supplier Segmentation, Fuzzy Set, Fuzzy Linguistic Preference Relations, Fuzzy C-Means
Abstract
In an environment characterized by its competitiveness, managing and monitoring relationships with suppliers are of the essence. Supplier management includes supplier segmentation. Existing literature demonstrates that suppliers are mostly segmented by computing their aggregated scores, without taking each supplier’s criterion value into account. The principle aim of this paper is to propose a supplier segmentation method that compares each supplier’s criterion value with exactly the same criterion of other suppliers. The Fuzzy Linguistic Preference Relations (LinPreRa) based Analytic Hierarchy Process (AHP) is first used to find the weight of each criterion. Then, Fuzzy c-means algorithm is employed to cluster suppliers based on their membership degrees. The obtained results show that the proposed method enhances the quality of the previous findings.
Cite This Paper
Pegah Sagheb Haghighi, Mahmoud Moradi, Maziar Salahi, "Supplier Segmentation using Fuzzy Linguistic Preference Relations and Fuzzy Clustering", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.5, pp.76-82, 2014. DOI:10.5815/ijisa.2014.05.08
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