Rough data envelopment analysis and its application to supply chain performance evaluation

Abstract

Supply chain (SC) performance evaluation is a complex decision-making problem involving various criteria under uncertainty situations. This paper studies the supply chain performance evaluation of a furniture manufacture industry in the southwest of China. We identify the main uncertainty factors affecting evaluation process, and then model and analyze them using our rough data envelopment analysis (RDEA) models. We create rough DEA by integrating classical DEA and rough set theory. The solution approach of rough DEA is discussed and employed to evaluate the supply chain network operation efficiency of the furniture manufacture industry. Then we give a practical example to illustrate the efficacy and efficiency of the rough DEA model and show how decision-making is improved by the insights the rough DEA model provides.