data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) with multiple inputs and outputs. the traditional dea treats decision making units under evaluation as black boxes and calculates their efficiencies with first inputs and last outputs. this carries the notion of missing some intermediate measures in the process of changing the inputs to...

data envelopment analysis (dea) is a mathematical technique to evaluate the performance of firms with multiple inputs and outputs. in conventional dea models, the efficiency scores of decision making units (dmus) with non-negative inputs and outputs are evaluated in a special period of time. however, in the real world there are situations wherein performance of firms must be evaluated in multip...

data envelopment analysis (dea) is a method to evaluate the relative efficiency of decision making units (dmus). in this method, the issue has always been to determine a set of weights for each dmu which often caused many problems. since the dea models also have the multi-objective linear programming (molp) problems nature, a rational relationship can be established between molp and dea problem...

this paper uses integrated data envelopment analysis (dea) models to rank all extreme and non-extreme efficient decision making units (dmus) and then applies integrated dea ranking method as a criterion to modify genetic algorithm (ga) for finding pareto optimal solutions of a multi objective programming (mop) problem. the researchers have used ranking method as a shortcut way to modify ga to d...

in this paper, we show that inverse data envelopment analysis (dea) models can be used to estimate output with fuzzy data for a decision making unit (dmu) when some or all inputs are increased and deficiency level of the unit remains unchanged.

data envelopment analysis (dea) is a managerial powerful tool for assess the performance of decision making units (dmus). nowadays, multi-objective dea models are an attractive technique for evaluation quantity and quality aspects of performance analysis. but these models are in static. in this paper, we want to present a proposed fuzzy dynamic multi-objective dea model in which data are changi...

for efficiency evaluation of some of the decision making units that have uncertain information, rough data envelopment analysis technique is used, which is derived from rough set theorem and data envelopment analysis (dea). in some situations rough data alter nonradially. to this end, this paper proposes additive rough–dea model and illustrates the proposed model by a numerical example.

supplier selection is a multi-criteria problem. this study proposes a hybrid model for supporting the suppliers’ selection and ranking. this research is a two-stage model designed to fully rank the suppliers where each supplier has multiple inputs and outputs. first, the supplier evaluation problem is formulated by data envelopment analysis (dea), since the regarded decision deals with uncertai...