Fuzzy data envelopment analysis: A discrete approach

Fuzzy data envelopment analysis: A discrete approach

Data envelopment analysis (DEA) as introduced by Charnes et al [3] is a linear programming technique that has widely been used to evaluate the relative efficiency of a set of homogenous decision making units (DMUs). In many real applications, the input-output variables cannot be precisely measured. This is particularly important in assessing efficiency of DMUs using DEA, since the efficiency sc...

Fuzzy data envelopment analysis: A fuzzy expected value approach

Performance assessment often has to be conducted under uncertainty. This paper proposes a ‘‘fuzzy expected value approach’’ for data envelopment analysis (DEA) in which fuzzy inputs and fuzzy outputs are first weighted, respectively, and their expected values then used to measure the optimistic and pessimistic efficiencies of decision making units (DMUs) in fuzzy environments. The two efficienc...

A fuzzy expected value approach under generalized data envelopment analysis

A Credibility Approach for Fuzzy Stochastic Data Envelopment Analysis (FSDEA)

It is well known that Data Envelopment Analysis (DEA) is a relative efficiency measurement tool, which uses optimization techniques to automatically calculate the weights assigned to the crisp deterministic multiple inputs and outputs of a set of the Decision Making Units (DMUs) being assessed. However, crisp deterministic data requirement delimits an application to the real world problems wher...

A fully fuzzy approach to data envelopment analysis

Data envelopment analysis (DEA) is a method to evaluate the efficiency of some decision making units which by using one or more inputs will make one or more outputs. In real world, most of the problems don’t have a certain mode. Fuzzy theory is one of the ways of considering uncertainty in the mathematical programming problems. In this study by using this idea, the DEA model on a fully fuzzy mo...