Dual models of interval DEA and its extension to interval data

By T. Entani, Y. Maeda, Hideo Tanaka. European Journal of Operational Research, 2002

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Review of efficiency ranking methods in data envelopment analysis (2017, methodology): “[85] based on the concept of virtual ADMUs.”
Interval efficiency assessment using data envelopment analysis (2005, methodology): “Entani et al.[6] proposed a DEA model with interval efficiencies measured from both the optimistic and the pessimistic viewpoints.”
Measuring the performances of decision-making units using interval efficiencies (2007, background): “[6] constructed the following upper and lower bounds mathematical programming model for DMU0:”
Ranking DMUs by ideal points with interval data in DEA (2011, background): “According to [8,15], models (18), (20) can be changed to the following problems:”
A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making (2011, methodology): “Fuzzy set algebra developed by Zadeh (1965) is the formal body of theory that allows the treatment of imprecise and vague estimates in uncertain environments. Zadeh (1965), p. 339 states ‘‘The notion of a fuzzy set provides a convenient point of departure for the construction of a conceptual framewo”
Interval data without sign restrictions in DEA (2014, background): “[28] proposed a DEA model with interval efficiencies measured from both the optimistic and the pessimistic viewpoints.”