A novel decision-making method using fuzzy DEA credibility constrained and RC index

Abstract

Decision-making based on expert’s opinion by data envelopment analysis (DEA) models requires crisp number. However, the assumption of expert might not always be accurate. This paper introduces fuzzy DEA credibility constrained and relative closeness (RC) index to cope with uncertainty data. The proposed approach transforms the traditional DEA models to be fuzzy events by using credibility measure. Furthermore, RC index was used to increase the discrimination power of traditional DEA. Two numerical examples with different credibility level are presented for demonstrate the proposed fuzzy DEA credibility constrained and RC index. The findings indicate that the credibility level impact on the RC index on both numerical examples. The increasing level of credibility value would drop the value of RC index.