A generalized fuzzy DEA/AR performance assessment model

Data envelopment analysis (DEA) is a non-parametric approach for performance assessment of a set of homogeneous decision making units (DMUs), which use similar inputs to produce similar outputs. Crisp data are commonly used in traditional DEA models. However, inputs and outputs have been observed whose values are imprecise in many cases. Meanwhile, the weights of inputs and outputs must be maintained in some ranges for the production mechanisms to work in reality. In this paper, a generalized fuzzy DEA model with assurance regions (GFDEA/AR) is proposed. Two linear programming models to determine the lower and upper bounds of fuzzy efficiency scores under given αα levels is proposed. The proposed GFDEA/AR model is then used to evaluate the performance of manufacturing enterprises in different cases.