Předpodmínění úloh kvadratického programování

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F07%3A00014979" target="_blank" >RIV/61989100:27240/07:00014979 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities

Popis výsledku v původním jazyce

The active set based MPRGP (modified proportioning with reduced gradient projection) for the solution of partially bound constrained quadratic programming problems turned out to be an important ingredient in development of scalable algorithms for the solution of variational inequalities by FETI and BETI domain decomposition methods. The algorithm was proved to have R-linear rate of convergence in terms of the spectral condition number of the Hessian matrix. Our presentation considers the preconditioningof MPRGP active set based algorithm with goal to get improved rate of convergence of the algorithm. We are interested in results which concern the overall rate of convergence, which requires not only the preconditioning of the solution of auxiliary linear solvers, but also the preconditioning of nonlinear steps. We first report improved bounds on the rate of convergence of MPRGP with preconditioning by conjugate projector applied to a model boundary variational inequality and give resul

Název v anglickém jazyce

Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities

Popis výsledku anglicky

The active set based MPRGP (modified proportioning with reduced gradient projection) for the solution of partially bound constrained quadratic programming problems turned out to be an important ingredient in development of scalable algorithms for the solution of variational inequalities by FETI and BETI domain decomposition methods. The algorithm was proved to have R-linear rate of convergence in terms of the spectral condition number of the Hessian matrix. Our presentation considers the preconditioningof MPRGP active set based algorithm with goal to get improved rate of convergence of the algorithm. We are interested in results which concern the overall rate of convergence, which requires not only the preconditioning of the solution of auxiliary linear solvers, but also the preconditioning of nonlinear steps. We first report improved bounds on the rate of convergence of MPRGP with preconditioning by conjugate projector applied to a model boundary variational inequality and give resul

Druh

D - Stať ve sborníku

CEP obor

BA - Obecná matematika

OECD FORD obor

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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

2007

Kód důvěrnosti údajů

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

Název statě ve sborníku

Computation Methods with Applications

ISBN

978-80-87136-00-3

ISSN

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e-ISSN

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Počet stran výsledku

1

Strana od-do

22-22

Název nakladatele

Institute of Computer Science AS CR

Místo vydání

Praha

Místo konání akce

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Datum konání akce

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Typ akce podle státní příslušnosti

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Kód UT WoS článku

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