In This paper a hybrid DEA method consisting of four phases for assigning the financial efficiency of commercial banks in India is used. This paper is based on panel data of banks for the period from 2011 to 2015. The DEA analysis based on hybrid method of DEA AND TOPSIS is used for ranking efficient Decision Making Units(DMUs) in Data Envelopment Analysis (DEA). However, since each of these me...

‎‎in the data envelopment analysis (dea) the efficiency of the units‎ ‎can be obtained by identifying the degree of the importance of the‎ ‎criteria (inputs-outputs).in dea basic models‎, ‎challenges are zero‎ ‎and unequal weights of the criteria when decision‎- ‎making units are‎ ‎evaluated‎. ‎one of the strategies applied to deal with these problems‎ ‎is using common weights of the each input...

data envelopment analysis (dea) is a non-parametric method for evaluating the relative technical efficiency for each member of a set of peer decision making units (dmus) with multiple inputs and multiple outputs. the original dea models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which interval scale data can appe...

in models of data envelopment analysis (dea), an optimal set of weights is generally assumed to represent the assessed decision making unit (dmu) in the best light in comparison to all the other dmus, and so there is an optimal set of weights corresponding to each dmu. the present paper, proposes a three stage method to determine one common set of weights for decision making units. then, we use...

In many applications, discrimination among decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA). The DEA models unable to discriminate between extremely efficient DMUs. Hence, there is a growing interest in improving discrimination power in DEA yet. The aim of this paper is ranking extreme efficient DMUs in DEA based on exp...

in this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (dmus) in stochastic data envelopment analysis (dea) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. it is shown that this deterministic model can be converted to a quadratic programming model. so fa...

banks are one of the most important financial sectors in order to the economic development of each country. certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. sometimes the performance of banks must be measured in the presence of undesirable and vague factors. for these reasons in the current paper a procedure based on data envelopment...

Data envelopment analysis (DEA) is a mathematical programming technique for identifying efficiency scores of decision making units (DMUs). Since DEA models cannot present efficient frontiers of PPS, in order to do this, we introduce a method for identifying efficient frontier for DMUs with interval data.