Pulse Transiently Chaotic Neural Network for Nonlinear Constrained Optimization

Li Ying1,2、 Cao Hongzhao3、 Hu Yunchang2、 Shang Xiuming1

Strategic Study of CAE ›› 2004, Vol. 6 ›› Issue (5) : 45-48.

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PDF(1862 KB)
Strategic Study of CAE ›› 2004, Vol. 6 ›› Issue (5) : 45-48.
Academic Papers

Pulse Transiently Chaotic Neural Network for Nonlinear Constrained Optimization

  • Li Ying1,2、 Cao Hongzhao3、 Hu Yunchang2、 Shang Xiuming1

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Abstract

Pulse Transiently Chaotic Neural Network (PTCNN) can find almost all optima including the part optima and the global with its abundance dynamical characteristic, when is used in nonlinear non-constrained optimization. The optimization problem is first unconstrained by virtue of non-differentiable exact penalty function, and is further solved by PTCNN. It is showed by an example that this method is efficient.

Keywords

PTCNN / penalty function / nonlinear constrained optimization

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Li Ying,Cao Hongzhao,Hu Yunchang,Shang Xiuming. Pulse Transiently Chaotic Neural Network for Nonlinear Constrained Optimization. Strategic Study of CAE, 2004, 6(5): 45‒48
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