An inexact proximal regularization method for unconstrained optimization |
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Authors: | Paul Armand Isaï Lankoandé |
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Affiliation: | 1.Faculté des Sciences et Techniques,XLIM Laboratory – University of Limoges,Limoges,France |
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Abstract: | We present a regularization algorithm to solve a smooth unconstrained minimization problem.This algorithm is suitable to solve a degenerate problem, when the Hessian is singular at a local optimal solution. The main feature of our algorithm is that it uses an outer/inner iteration scheme. We show that the algorithm has a strong global convergence property under mild assumptions. A local convergence analysis shows that the algorithm is superlinearly convergent under a local error bound condition. Some numerical experiments are reported. |
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