<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>We present a random perturbation of the projected variable metric method for solving linearly constrained nonsmooth (i.e., nondifferentiable) nonconvex optimization problems, and we establish the convergence to a global minimum for a locally Lipschitz continuous objective function which may be nondifferentiable on a countable set of points. Numerical results show the effectiveness of the proposed approach.</p></abstract>

We present a random perturbation of the projected variable metric method for solving linearly constrained nonsmooth (i.e., nondifferentiable) nonconvex optimization problems, and we establish the convergence to a global minimum for a locally Lipschitz continuous objective function which may be nondifferentiable on a countable set of points. Numerical results show the effectiveness of the proposed approach.

Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints

Department of Mathematics, Faculty of Science, Jazan University, P.B. 2097, Jazan, Saudi Arabia

Laboratory of Study and Research in Applied Mathematics, Mohammadia School of Engineers, Mohammed V Agdal University, Ab Ibn sina, BP 765, Agdal, Rabat, Morocco

National Institute for Applied Sciences, Rouen Avenue de l'Université, BP 8, Saint-Etienne du Rouvray, France

International Journal of Applied Mathematics and Computer Science

We present a random perturbation of the projected variable metric method for solving linearly constrained nonsmooth (i.e., nondifferentiable) nonconvex...

Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints

Publié en ligne: 22 juin 2011

Pages: 317 - 329

DOI: https://doi.org/10.2478/v10006-011-0024-z

Mots clés
global optimization, linear constraints, variable metric method, stochastic perturbation, nonsmooth optimization

This content is open access.

Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints

Publié en ligne: 22 juin 2011

Pages: 317 - 329

DOI: https://doi.org/10.2478/v10006-011-0024-z

Mots clésglobal optimization, linear constraints, variable metric method, stochastic perturbation, nonsmooth optimization

This content is open access.

Mots clés
global optimization, linear constraints, variable metric method, stochastic perturbation, nonsmooth optimization