Data envelopment analysis (DEA) is a useful mathematical tool for evaluating the performance of production units and ranking their relative efficiency. In many real-world applications, belong to several separate groups also consist sub-units. this paper, we introduce new method group efficiency two-stage systems. To end, some DEA models are introduced systems based on average weakest criteria. ...

One of the important goals of banks as important economic enterprises of any country is to increase economic efficiency. One of the important goals of banks as important economic enterprises of any country is to increase economic efficiency. The classical approach to data envelopment analysis models takes into account the linear valuation function for all indicators. But linear valuation in man...

for better guiding a system, senior managers should have accurate information. using data envelopment analysis (dea) help managers in this objective. thus, many investigations have been made in order to find the most productive scale size (mpss) for the evaluating decision making units (dmus). in this paper we consider this case where there exist subsets of input and output variables to be inte...

Data Envelopment Analysis (DEA) provides means for piecewise linear approximation of production functions. To improve the fit to the data we propose to improve the flexibility of the frontier by extending DEA towards a more general piecewise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). In contrast to the linear approximation, the quadratic approximation allows for...

This paper presents a new robust two-stage Data Envelopment Analysis (DEA) for efficiency evaluation of the electricity power production and distribution companies. DEA has been widely used for benchmarking the electricity companies. Traditional studies in DEA consider systems as a whole when measuring the efficiency, ignoring the operation of individual processes within a system. To tackle thi...

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...