Performance Measurement Using DEA in a Fully Fuzzified Environment

Data envelopment analysis (DEA) is a considerable mathematical programming technique for measuring the relative efficiencies of a set of decision making units (DMUs) with multiple and multiple outputs. The conventional are basically limited to definite input and output data. However, real applications of production process potentially consist of many ambiguous and vague factors. This paper carries out a research on DEA in the fully imprecise environment where, in addition to input and output data, variables are fuzzy numbers. We present a fully fuzzified linear programming problem to gain the fuzzy efficiency scores for assessing DMUs. A multi-objective linear programming (MOLP) problem as a solving approach is utilised to find an optimal solution for the fuzzy DEA model proposed in this study. We ultimately attempt to demonstrate that the developed method is more efficient and applicable in comparison with the existing methods in the literature.

Data envelopment analyisi, Efficiency, Fuzzy programming, Multi-objective linear programming.