A Recurrent Neural Network Model for solving CCR Model in Data Envelopment Analysis
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Abstract:
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 a single-layer structure. A numerical example shows that the proposed model is effective to solve CCR model in DEA.
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Journal title
volume 11 issue 1
pages 1- 7
publication date 2019-06-01
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