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2006 | 16 | 4 | 463-474

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Random perturbation of the variable metric method for unconstrained nonsmooth nonconvex optimization

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We consider the global optimization of a nonsmooth (nondifferentiable) nonconvex real function. We introduce a variable metric descent method adapted to nonsmooth situations, which is modified by the incorporation of suitable random perturbations. Convergence to a global minimum is established and a simple method for the generation of suitable perturbations is introduced. An algorithm is proposed and numerical results are presented, showing that the method is computationally effective and stable.








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  • Ecole Mohammadia d'Ingenieurs, LERMA, Avenue Ibn Sina BP765-Agdal, Rabat, Morocco
  • Ecole Mohammadia d'Ingenieurs, LERMA, Avenue Ibn Sina BP765-Agdal, Rabat, Morocco
  • LMR - UMR 6138 CNRS, INSA-Rouen, Avenue de l'Universite BP 8, Saint-Etienne du Rouvray, France


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