Data Envelopment Analysis (DEA) was developed to help compare the relative performance of decision-making units. It is a non-parametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. DEA generates an efficiency score between 0 and 1 for each unit...

a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters the comparison among dmus on a common base. for dealing with this difficulty and assessing all the dmus on the sam...

data envelopment analysis (dea) is an approach for evaluating performances of decision making units (dmus). the performances of dmus are affected by the amount of sources that dmus used. usually increases in inputs cause increases in outputs. however, there are situations where increases in one or more inputs generate a reduction in one or more outputs. in such situations there is congestion in...

Data Envelopment Analysis (DEA) is a relatively new “data oriented” non-parametric approach for evaluating the performance of complex entities called Decision Making Units (DMUs) which convert multiple inputs into multiple outputs. DEA as a linear programming procedure computes a comparative ratio of outputs to inputs for each DMU, which is reported as the relative efficiency score. In a relati...

Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. This paper shows the method of Discriminant Analysis (DA), on Imprecise Data by Data Envelopment 724 F. Hosseinzadeh Lotfi et al Analysis (DEA). DEA-Discriminant Analysis (DEA-DA) is designed to identify the existence or n...

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...

data envelopment analysis (dea) is a method to measure relative efficiency of a set of decision-making units (dmus) which uses multiple inputs and produces multiple outputs. in the conventional dea, crisp inputs and outputs are fundamentally necessary. but the observed values of inputs and outputs in real-world problems are sometimes imprecise. thus, performance measurement often needs to be do...

this research identifies returns to scale (rts) of efficient decision making units (dmus) with desirable (good) and undesirable (bad) inputs and outputs by presenting a new dea (data envelopment analysis) approach. in this study, we first introduce a new input-output oriented model to determine efficient dmus in the presence of undesirable factors and then, returns to scale of these dmus are es...

A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective...

efficiency calculations for units belonging to one group according to data envelopment analysis widely have received attention; while experiences related to efficiency comparison of several groups consisted of decision making units is restricted. kao's parallel system network dea model that has been designated aimed at such a comparison, practically leads to accomplish comparison among uni...