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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F07%3A00014979%21RIV08-AV0-27240___
rdf:type
skos:Concept n16:Vysledek
dcterms:description
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 preconditioning of 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 results of numerical 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 preconditioning of 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 results of numerical V prezentaci ukazujeme předpodmínění algoritmu MPRGP s cílem zlepšit rychlost konvergence. Předpodmínění zasahuje všechny kroky algoritmu, tedy i ty nelineární.
dcterms:title
Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities Předpodmínění úloh kvadratického programování
skos:prefLabel
Předpodmínění úloh kvadratického programování Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities
skos:notation
RIV/61989100:27240/07:00014979!RIV08-AV0-27240___
n3:strany
22-22
n3:aktivita
n15:Z n15:P
n3:aktivity
P(1ET400300415), P(GA201/07/0294), Z(MSM6198910027)
n3:dodaniDat
n4:2008
n3:domaciTvurceVysledku
n12:5021391
n3:druhVysledku
n9:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n13:predkladatel
n3:idSjednocenehoVysledku
443519
n3:idVysledku
RIV/61989100:27240/07:00014979
n3:jazykVysledku
n6:eng
n3:klicovaSlova
quadratic programming; rate of convergence; bound constraints
n3:klicoveSlovo
n5:rate%20of%20convergence n5:quadratic%20programming n5:bound%20constraints
n3:kontrolniKodProRIV
[0B01E55CB5D9]
n3:mistoVydani
Praha
n3:nazevZdroje
Computation Methods with Applications
n3:obor
n14:BA
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
2
n3:projekt
n19:1ET400300415 n19:GA201%2F07%2F0294
n3:rokUplatneniVysledku
n4:2007
n3:tvurceVysledku
Dostál, Zdeněk Domorádová, Marta
n3:zamer
n17:MSM6198910027
s:numberOfPages
1
n11:hasPublisher
Ústav informatiky AV ČR
n8:isbn
978-80-87136-00-3
n18:organizacniJednotka
27240