| Date de soumission: | 09-02-2021 |
|---|---|
| Année de Publication: | 2018 |
| Entité/Laboratoire | Autres Laboratoires |
| Document type : | Article |
| Discipline(s) : | Mathématiques |
| Titre | Algorithms for asymptotically exact minimizations in Karush-Kuhn-Tucker methods. |
|---|---|
| Auteurs | DEGLA Guy [2], |
| Journal: | Journal of Mathematics Research |
| Catégorie Journal: | Internationale |
| Impact factor: | |
| Volume Journal: | 10 |
| DOI: | 10.5539/jmr.v10n2p36 |
| Resume | We provide two new algorithms with applications to asymptotically exact minimizations with inequalities constraints. These results generalize and improve the works of Andreani, Birgin, Martinez and Schuverdt on minimization with equality constraints. Numerical examples show that our proposed analysis gives convergence results. |
| Mots clés | nonlinear programming, augmented lagrangian methods, numerical experiments, approximate KKT point. |
| Pages | 36 - 54 |
| Fichier |