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 shows itself in the
evaluation process of 23 provincial gas companies considering the higher input and output
rates of each provincial gas company. Based on this and for solving this problem, an
integrative model composed of Performance Predictor Neural Networks and Data
Envelopment Analysis are used in this research that contributed to the increased power of
evaluation, separability, and due ranking of companies.
کلید واژگان :
Data Envelopment Analysis, Artificial Neural Networks(ANNs), Neuro/DEA, Technical Efficiency, CCR Model of the Input Oriented
