A Hybrid model based on neural network and Data Envelopment Analysis model for Evaluation of unit Performance

Abstract

Efficiency and evaluation is one of the main and most important demands of organizations, companies and institutions. As these organizations deal with a large amount of data, therefore, it is necessary to evaluate them on the basis of scientific methods to improve their efficiency. Data envelopment analysis is a suitable method for measuring the efficiency and performance of organizations. This paper has been conducted to evaluate the performance and efficiency of decision making units. First, using the data envelopment analysis, the BCC output oriented model, these units are ranked and the shortcoming of the model in terms of efficacy measurement and separation are determined. Then, to overcome such problems, a combined method of data envelopment analysis; the BCC output oriented model and artificial neural network are used to evaluate the efficiency of these units and finally the results of the two models are compared.Given the efficiency obtained with the BCC output oriented method, it was observed that the amount of efficiency for some units which leads for these units not to be ranked but using the proposed NEURO-DEA method, no two units have the same efficiency and given the obtained efficiency, these units can be evaluated and ranked.

Keywords

• Efficiency
• Performance Evaluation
• Data Envelopment Analysis
• Artificial Neural Network (ANNS)
• BCC Output Oriented Model