Efficiency Measure by Fuzzy Data Envelopment Analysis Model

Abstract Data envelopment analysis (DEA) is a non-parametric technique to measure the relative efficiencies of a set of decision making units (DMUs) with common crisp inputs and outputs. Input and output data of DMUs often fluctuate. These fluctuating data can be represented as linguistic variable characterized by fuzzy numbers. This paper attempts to extend the traditional DEA model to a fuzzy framework, thus proposing a fuzzy DEA model based on -cut approach to deal with the efficiency measuring and ranking problem with the given fuzzy input and output data. Finally, a numerical example is presented to illustrate the fuzzy DEA model. Since the efficiency measures are expressed by membership functions rather than by crisp values, more information is provided for management. By extending to fuzzy environment, the DEA approach is made more powerful for application.