Fuzzy approach to supply chain management

Keywords: Supply Chain, Fuzzy Sets, Fuzzy Measures, Fuzzy Entropy

Abstract

During recent years, the supply chain performance management has become a key strategic consideration. Many manufacturers seek to collaborate with their suppliers and customers in order to upgrade their competitiveness and management performance. Because of complexity, uncertainty and vagueness inherent in supply chains, performance measurement using fuzzy approach was also identified as a new research direction. The main aim of the paper is focused on evaluation of logistic dimensions (sets of logistic indicators) in supply chain, where the uncertainty arises from the inability to perform adequate measurement, and deals with application of fuzzy approach, that provides a formal method for modeling imprecise, vagueness or incomplete relationships inherent in supply chains. Gathered data from questionnaires are analyzed by cluster analysis. Afterwards fuzzy methods are used evaluations of basic five dimensions, which contain several numbers of logistic indicators. The new methodology adopted from Soyer, Kabak, Asan (2007) research based on the intersection of fuzzy sets and fuzzy entropy method has been applied to evaluations in a case study. Results are afterwards modified by a applying of different membership functions, and changes of dimensions measures are analyzed. Finally supply chain modifying by adding new companies with capability of bind to supply chain are examined. New results of evaluation are compared according to new companies’ membership to different clusters.

References

Ali, YM., Zhang, LC, (1999). Surface roughness prediction of ground components using a fuzzy logic approach. Journal of materials processing technology, 89-90, 561-568.

Published
2012-11-21
Section
Articles