Abstract
Data envelopment analysis (DEA) is an effective technique for measuring the relative efficiency of a set of homogeneous decision-making units (DMUs). The generalized data envelopment analysis (GDEA) model, which contains four basic DEA models, is an important DEA model. When calculating the efficiency of each DMU, the GDEA model requires crisp input and output data, which are often difficult to obtain in real-world problems. In this paper, we will employ the credibility theory and chance-constrained programming to evaluate the efficiency of each DMU in fuzzy GDEA (FGDEA) model. We first introduce the credibility GDEA (CGDEA) model, and then discuss its crisp equivalent form in some special cases. At last, a numerical experiment is given to illustrate the efficiency of the CGDEA model.
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