Data Envelopment Analysis (DEA) is one of the best methods for measuring the efficiency and productivity of Decision Making Units (DMU). Evaluating the efficiency of DMUs which have two or several stages by using the conventional DEA models, is equal to consider them as black box. This method, omits the effect of intermediate measure on efficiency. Therefore, just the first network inputs and t...

In this paper, grey system theory and DEA are combined to establish a grey DEA model. In traditional DEA model, Input and output values of decision-making groups are all real numbers and real variables. They are replaced by grey numbers and grey variables in grey DEA model respectively. Using positioning solution method of grey linear programming, we prove the necessary condition for grey effec...

data envelopment analysis (dea) is an eciency measurement tool for evaluation of similar decision making units (dmus). in dea, weights are assigned to inputs and outputs and the absolute eciency score is obtained by the ratio of weighted sum of outputs to weighted sum of inputs. in traditional dea models, this measure is also equivalent with relative eciency score which evaluates dmus in com...

In the performance evaluation process, using the classic data envelopment analysis (DEA) models, decision making units (DMUs) are considered as black boxes. While in many cases and different applications such as investment funds, banks, insurance companies, etc., DMUs have a network structure. In addition, in many network structures, some of the indicators used to calculate the efficiency...

in the process of production, some of the inputs are fixed and cannot easily be changed, such as work hours of workers and hours of administrative or work, these types of inputs are fixed and others are variables. in this paper, by considering some inputs or outputs which are limited, their amounts must be integrated; this concept for integer data is extended. we show the importance of subject ...

Abstract: In the conventional data envelopment analysis (DEA), all the data assumes the form of crisp numerical values. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Some researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA by constructing linear programming (LP) models with ...

this paper reports a survey and case study research outcomes on the application of data envelopment analysis (dea) to the ranking method of european foundation for quality management (efqm) business excellence model in iran’s automotive industry and improving benchmarking process after assessment. following the global trend, the iranian industry leaders have introduced the efqm practice to thei...

data envelopment analysis (dea) is a technique used to evaluate the relative efficiency of comparable decision making units (dmus) with multiple input-output. it computes a scalar measure of efficiency and discriminates between efficient and inefficient dmus. it can also provide reference units for inefficient dmus without consideration of the decision makers’ (dms) preferences. in this paper, ...

performance evaluation of universities is an important issue between researchers. classic data envelopment analysis (dea) models with deterministic data have been used by many authors to measure efficiency of universities in different countries. however, dea with stochastic data are, rarely used to measure efficiency of universities. in this paper, input oriented model in stochastic data envelo...