An optimal algorithm for bound and equality constrained quadratic programming problems with bounded spectrum

dc.contributor.authorDostál, Zdeněk
dc.date.accessioned2007-01-12T14:28:15Z
dc.date.available2007-01-12T14:28:15Z
dc.date.issued2006
dc.description.abstract-enAn implementation of the recently proposed semi-monotonic augmented Lagrangian algorithm for solving the large convex bound and equality constrained quadratic programming problems is considered. It is proved that if the algorithm is applied to the class of problems with uniformly bounded spectrum of the Hessian matrix, then the algorithm finds an approximate solution at O(1) matrix-vector multiplications. The optimality results are presented that do not depend on conditioning of the matrix which defines the equality constraints. Theory covers also the problems with dependent constraints. Theoretical results are illustrated by numerical experiments.en
dc.identifier.citationComputing. 2006, vol. 78, no. 4, p. 311-328.en
dc.identifier.doi10.1007/s00607-006-0184-0
dc.identifier.issn0010-485X
dc.identifier.issn1436-5057
dc.identifier.locationNení ve fondu ÚKen
dc.identifier.urihttp://hdl.handle.net/10084/59633
dc.identifier.wos000242885100002
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesComputingen
dc.relation.urihttp://dx.doi.org/10.1007/s00607-006-0184-0en
dc.subjectquadratic programmingen
dc.subjectbound and equality constraintsen
dc.subjectaugmented Lagrangiansen
dc.subjectoptimal algorithmsen
dc.titleAn optimal algorithm for bound and equality constrained quadratic programming problems with bounded spectrumen
dc.typearticleen

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