Using fuzzy programming and multi-objective DEA models for preferred target setting

Data envelopment analysis (DEA) is a mathematical programming technique estimating relative efficiency of a group of homogenous decision making units (DMUs). In order to improve the performance of inefficient DMUs, a target setting procedure can be offered using DEA models. In conventional DEA models, the DM‘s view is ignored in process of evaluation and target setting and the analysis is done only based on the input-output level of observed DMUs. Using fuzzy programming approaches, this study will established the equivalence between DEA and multiple objective linear programming (MOLP) and then it presents a method to approximate a favored benchmark for the input and output levels, considering the DM‘s view in the process of evaluation of DMUs. A benchmark for each DMU is presented that is to be close to the manager s goals as far as possible.

Keywords:

DEA , Fuzzy Programming , Target Setting , MOLP