An accelerated augmented Lagrangian algorithm with adaptive orthogonalization strategy for bound and equality constrained quadratic programming and its application to large-scale contact problems of elasticity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F21%3A10248065" target="_blank" >RIV/61989100:27740/21:10248065 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/21:10248065

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0377042721001850" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0377042721001850</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cam.2021.113565" target="_blank" >10.1016/j.cam.2021.113565</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An accelerated augmented Lagrangian algorithm with adaptive orthogonalization strategy for bound and equality constrained quadratic programming and its application to large-scale contact problems of elasticity

Popis výsledku v původním jazyce

Augmented Lagrangian method is a well established tool for the solution of optimization problems with equality constraints. If combined with effective algorithms for the solution of bound constrained quadratic programming problems, it can solve efficiently very large problems with bound and linear equality constraints. The point of this paper is to show that the performance of the algorithm can be essentially improved by enhancing the information on the free set of current iterates into the reorthogonalization of equality constraints. The improvement is demonstrated on the numerical solution of a large problem arising from the application of domain decomposition methods to the solution of discretized elliptic variational inequality describing a variant of Hertz&apos;s two-body contact problem. (C) 2021 Elsevier B.V. All rights reserved.

Název v anglickém jazyce

An accelerated augmented Lagrangian algorithm with adaptive orthogonalization strategy for bound and equality constrained quadratic programming and its application to large-scale contact problems of elasticity

Popis výsledku anglicky

Augmented Lagrangian method is a well established tool for the solution of optimization problems with equality constraints. If combined with effective algorithms for the solution of bound constrained quadratic programming problems, it can solve efficiently very large problems with bound and linear equality constraints. The point of this paper is to show that the performance of the algorithm can be essentially improved by enhancing the information on the free set of current iterates into the reorthogonalization of equality constraints. The improvement is demonstrated on the numerical solution of a large problem arising from the application of domain decomposition methods to the solution of discretized elliptic variational inequality describing a variant of Hertz&apos;s two-body contact problem. (C) 2021 Elsevier B.V. All rights reserved.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of computational and applied mathematics

ISSN

0377-0427

e-ISSN

—

Svazek periodika

394

Číslo periodika v rámci svazku

1 October 2021

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

—

Kód UT WoS článku

000645665800018

EID výsledku v databázi Scopus

2-s2.0-85104134705