A Novel Neurodynamic Model for Data Envelopment Analysis: A Case Study on Iran's Olympic Sports Caravan

Data envelopment analysis (DEA) is one of the non-parametric approaches for evaluating efficiency. The present paper investigates a novel recurrent neural network (RNN) model for solving DEA problems. To the best of our knowledge, there is no attempt for this kind of problem using RNN. Thus, this paper is going to show the effectiveness of RNN models for solving DEA problems. As a matter of fact, we give a novel RNN model to solve a general linear programming problem. Moreover, the stability in the sense of Lyapunov for the developed RNN model is proved. Finally, to show the performance of the method we consider a general case model and a case study on Iran's Olympic Sports Caravan and solve with the novel proposed RNN model.