An Inverse BCC Model for Evaluating and Ordering Decision-Making Units under Fuzziness

One of the most ‎prevalent problems in linear programming as one of the convenient models in the field of operation research ‎‎environment is Data Envelopment Analysis (DEA), which supports the ‎efficiency of ‎‎Decision-Making Units (DMUs). Usually, accurate data are common; however, in ‎the real world, we are facing an inaccurate ‎situation. In this paper, a new ‎model for assessing DMUs in a fuzzy environment is presented; we ‎consider the inverse DEA ‎model with the variable return to scale with fuzzy numbers for fluctuating ‎data. A case study is given to ‎illustrate its performance.