Reduction and Optimization of Supplier Risk Indicators Based on Rough Set

The determination of supplier risk indicators is complex. Using vast data from SAP system of the enterprise, risk warning indicators can be reduced and optimized by the method of rough set. First of all, extract historical data from SAP system, and determine the discrete rules as excellent, good, moderate, and poor for each risk indicators to construct knowledge set which can be used for rough set operation. Then, using rough set theory to divide decision attribute set into equivalence classes, reduce non essential attributes, and calculate the dependence and importance degree for each essential attributes. After the normalization for all essential attributes, the reduced and optimized indicators for supplier risk evaluation system can be reached.