RANDOM PERTURBATION OF THE VARIABLE METRIC METHOD FOR UNCONSTRAINED NONSMOOTH NONCONVEX OPTIMIZATION
Abdelkrim El Mouatasim, Rachid Ellaia, Eduardo Souza de Cursi · 2006
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.