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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Supplier Selection: A Hybrid Approach Using ELECTRE and Fuzzy Clustering
verfasst von : Amir Hossein Azadnia, Pezhman Ghadimi, Muhamad Zameri Mat Saman, Kuan Yew Wong, Safian Sharif
Erschienen in: Informatics Engineering and Information Science
Verlag: Springer Berlin Heidelberg
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Vendor selection is a strategic issue in supply-chain management for any organization to identify the right supplier. Such selection in most cases is based on the analysis of some specific criteria. Most of the researches so far concentrate on multi-criteria decision making (MCDM) analysis. However, it incurs a huge computational complexity when a large number of suppliers are considered. So, data mining approaches would be required to convert raw data into useful information and knowledge. Hence, a new hybrid model of MCDM and data mining approaches was proposed in this research to address the supplier selection problem. In this paper, Fuzzy C-Means (FCM) clustering as a data mining model has been used to cluster suppliers into groups. Then, Elimination and Choice Expressing Reality (ELECTRE) method has been employed to rank the suppliers. The efficiency of this method was revealed by conducting a case study in an automotive industry.