Developing Common Set of Weights with Considering Nondiscretionary Inputs and Using Ideal Point Method

Deriving Common Set of Weights in the Presence of the Undesirable Inputs: A DEA based Approach

Data Envelopment Analysis (DEA) as a non-parametric method for efficiency measurement allows decision making units (DMUs) to select the most advantageous weight factors in order to maximize their efficiency scores.  In most practical applications of DEA presented in the literature, the presented models assume that all inputs are fully desirable. However, in many real situations undesirable inpu...

Ranking of units by anti-ideal DMU with common weights

Data envelopment analysis (DEA) is a powerful technique for performance evaluation of decision making units (DMUs). One of the main objectives that is followed in performance evaluation is discriminating among efficient DMUs to provide a complete ranking of DMUs. DEA successfully divides them into two categories: efficient DMUs and inefficient DMUs. The DMUs in the efficient category have ident...

Common weights for the evaluation of decision-making units with nonlinear virtual inputs and outputs

In this paper, by investigating the common weights concept and DEA models with nonlinear virtual inputs/outputs, we introduce a model for evaluating the decision making units with nonlinear virtual inputs and outputs based on the common weights.

deriving common set of weights in the presence of the undesirable inputs: a dea based approach

data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

Eciency Measurement of Multiple Components units in Data Envelopment Analysis Using Common Set of Weights