Abstract
Supply chain and industrial cluster are the results of competition economy. Clustering analysis enable more efficient supply chain management practices. In this paper, we focus our dis-cussion on the rough set theory for clustering supplier chain management. We propose ROSMAN (ROugh Set approach for clustering Supplier chain MANagement), an alternative algorithm for clustering supplier base management based on rough set theory taking into account maximal at-tributes dependencies in an information system. Experimental result on a supplier data set shows that ROSMAN technique is better with the baseline supplier base management clustering algorithm with respect to computational complexity and clusters purity.
