Algorithms for asymptotically exact minimizations in Karush-Kuhn-Tucker methods.

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AuteurDEGLA, AYMARD GUY
Date d'ajout2026-06-02T16:06:57Z
Date de disponibilite2026-06-02T16:06:57Z
Date de publication2018
ResumeWe 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.
DOI10.5539/jmr.v10n2p36
Autre identifiantBECDB-6748
URIhttps://dspace.uac.bj/handle/123456789/6115
Languefr
Fait partie deJournal of Mathematics Research
Sujetnonlinear programming
Sujetaugmented lagrangian methods
Sujetnumerical experiments
Sujetapproximate KKT point
TitreAlgorithms for asymptotically exact minimizations in Karush-Kuhn-Tucker methods.
TypeArticle

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