
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.
Pulse Transiently Chaotic Neural Network for Nonlinear Constrained Optimization
Li Ying1,2、 Cao Hongzhao3、 Hu Yunchang2、 Shang Xiuming1
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.
PTCNN / penalty function / nonlinear constrained optimization
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