A new fuzzy complete ranking of DMUs with undesirable outputs

Efficiency analysis is performed not only to estimate the current level of efficiency, but also to provide information on how to remove inefficiency, that is, to obtain benchmarking information. Data Envelopment Analysis (DEA) was developed in order to satisfy both objectives and the strength of its benchmarking analysis gives DEA a unique advantage over other methodologies of efficiency analysis. Data envelopment analysis is an efficiency estimation technique, but it can beused for solving many problems of management such as ranking of DMUs. Ranking DMUs is an important issue in DEA studies. Traditional data envelopment analysis models do not deal with imprecise data an assume that the data for all inputs and outputs are known exactly. In real worldsituations, however, this assumption may not always be true. The motivation of this study is to develop a new fuzzy ranking model with undesirable outputs. We use possibility approach is chosen to convert the fuzzy model to a crisp model.

Keywords:

Data envelopment analysis , Ranking , Fuzzy