generalized fuzzy dea cross-efficiency evaluation based on pareto improvement

Cross efficiency evaluation, as an extension tool of dea has been widely applied in evaluating and ranking dmus. the cross efficiency scores generated may not be pareto optimal. cross efficiency evaluation approach based on pareto improvement proposed for solve this problem which contains models and an algorithm. this paper studies these models for fuzzy data. fuzzy data envelopment analysis (fdea) models emerge as another class of dea models to account for imprecise inputs and outputs for decision making units. although several approaches for solving fuzzy dea models have been developed, numerous deficiencies including the α-cut approaches and types of fuzzy numbers must still be improved. this paper proposes generalized cross efficiency evaluation based on pareto improvement in fuzzy data envelopment analysis