International Journal of applied mathematics and computer science

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Paper details

Number 4 - December 2006
Volume 16 - 2006

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

Abdelkrim El Mouatasim, Rachid Ellaia, José E. Souza de Cursi

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.

nonconvex optimization, stochastic perturbation, variable metric method, nonsmooth optimization, generalized gradient