a new algorithm for classification of dmus to efficient and inefficient units in data envelopment analysis is presented. this algorithm uses the non-archimedean charnes-cooper-rhodes[1] (ccr) model. also, it applies an assurance value for the non-archimedean                          using only simple computations on inputs and outputs of dmus (see [18]). the convergence and efficiency of the ne...

credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. for this sake, in this paper a data envelopment analysis- discriminant analysis (dea-da) approach is us...

background: nowadays, restriction on access and optimum use of resources is the main challenge of development in all organizations. therefore, the aim of this study was to determine the technical efficiency and its factors, influencing hospitals of tehran. methods: this research was a descriptive-analytical and retrospective study conducted in 2014-2015. fifty two hospitals with public, private...

In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...

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 technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

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 technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

one of the biggest problems of using data envelopment analysis for the evaluation of performance is the weakness of the separability for the decision maker units. this problem is generalizable because of the lower quantity of units in comparison with the ¬input and output quantities of the model [1]. this matter considerably reveals itself in the evaluation process of 23 provincial gas companie...

Data envelopment analysis (DEA) is a nonstochastic and nonparametric linear programming technique where a set of units are evaluated according to their input consumption and output production (Charnes et al. (1978)). Given that DEA efficiency analysis can be influenced by the presence of outliers, Banker and Chang (2006) proposed a method to detect atypical units through the super-efficiency mo...