Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints
Abdelkrim El Mouatasim; Rachid Ellaia; Eduardo Souza de Cursi
International Journal of Applied Mathematics and Computer Science (2011)
- Volume: 21, Issue: 2, page 317-329
- ISSN: 1641-876X
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topAbdelkrim El Mouatasim, Rachid Ellaia, and Eduardo Souza de Cursi. "Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints." International Journal of Applied Mathematics and Computer Science 21.2 (2011): 317-329. <http://eudml.org/doc/208050>.
@article{AbdelkrimElMouatasim2011,
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.},
author = {Abdelkrim El Mouatasim, Rachid Ellaia, Eduardo Souza de Cursi},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {global optimization; linear constraints; variable metric method; stochastic perturbation; nonsmooth optimization},
language = {eng},
number = {2},
pages = {317-329},
title = {Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints},
url = {http://eudml.org/doc/208050},
volume = {21},
year = {2011},
}
TY - JOUR
AU - Abdelkrim El Mouatasim
AU - Rachid Ellaia
AU - Eduardo Souza de Cursi
TI - Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints
JO - International Journal of Applied Mathematics and Computer Science
PY - 2011
VL - 21
IS - 2
SP - 317
EP - 329
AB - 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.
LA - eng
KW - global optimization; linear constraints; variable metric method; stochastic perturbation; nonsmooth optimization
UR - http://eudml.org/doc/208050
ER -
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