This paper considers a parametric global optimization constrained and unconstrained problem in a real Hilbert space. We suppose that the gradient of the cost functional is Lipschitz continuous but not smooth function. The suitable choice of the parameters implies the linear or superlinear (supergeometric) convengence of the iterative method.
Parametric method for global optimization problems in Hilbert Spaces
DE MARCHI, STEFANO;
2006
Abstract
This paper considers a parametric global optimization constrained and unconstrained problem in a real Hilbert space. We suppose that the gradient of the cost functional is Lipschitz continuous but not smooth function. The suitable choice of the parameters implies the linear or superlinear (supergeometric) convengence of the iterative method.
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