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Supplier Evaluation Using Fuzzy Inference Systems

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 313))

Abstract

Supplier selection is an important area of decision making in manufacturing and service industries, mainly for large and medium companies—either multinational (MNCs) or local. As sustainability in terms of economic, environmental, and social aspects has gained world-wide focus in supply chain management, this dimension deserves due attention in supplier selection decision. In real life applications, the importance of supplier selection criteria is different and depends on the circumstances and situations and each organization may consider its individual relative importance of the criteria. The relative importance of the criteria and also the suppliers’ performance with respect to these criteria would be verified with the relevant decision makers. So, the supplier selection decision involves a high degree of vagueness and ambiguity in practice. This chapter takes the aforesaid issues into account and proposes a modular FIS method for supplier selection problem. To handle the subjectivity of decision makers’ preferences, fuzzy set theory is applied. The applicability and feasibility of the proposed method are tested through a real-life supplier selection problem.

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Correspondence to Atefeh Amindoust .

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Amindoust, A., Saghafinia, A. (2014). Supplier Evaluation Using Fuzzy Inference Systems. In: Kahraman, C., Öztayşi, B. (eds) Supply Chain Management Under Fuzziness. Studies in Fuzziness and Soft Computing, vol 313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53939-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-53939-8_1

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