Efficiency ranking of DMUS with fuzzy data

The aim of this research is to present an integrated method of data envelopment analysis (DEA) and fuzzy TOPSIS technique based on similarity to the ideal solution for the complete ranking of decision making units in a fuzzy environment. In this method, DMUs are considered as alternatives, input variables as cost criteria (negative attributes) and output variables as benefit criteria (positive attributes); Because the efficiency of a DMU increases by increasing the values of the outputs and decreasing the values of the inputs. In addition, the presented method can be used to rank DMUs with unfavorable outputs. The efficiency and simplicity of this method have been investigated via examples and case study. Also, the obtained results have been compared with the results in related articles