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...

a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights that are the most advantages 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 same s...

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...

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper introduces a neural network backpropagation Data Envelopment Analysis. Neural network requirements of computer memo...

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...

in the real world there are groups which composed of independent units. the conventional data envelopment analysis(dea) model treats groups as units, ignoring the operation of individual units within each group.the current paper, investigates parallel system network approach proposed by kao and modifies it. as modi ed kao' model is more eligible to recognize ecient groups, a new ranking m...

data envelopment analysis (dea) is a non-parametric method for assessing relative efficiency of decision-making units (dmus). every single decision-maker with the use of inputs produces outputs. these decision-making units will be defined by the production possibility set. resource allocation to dmus is one of the concerns of managers since managers can employ the results of this process to all...

One of the difficulties of Data Envelopment Analysis(DEA) is the problem of deciency discriminationamong efficient Decision Making Units(DMUs) and hence, yielding large number of DMUs as efficientones. The main purpose of this paper is to overcome this inability. One of the methods for rankingefficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this pape...