Zobrazit minimální záznam

dc.contributor.authorKučera, Radek
dc.date.accessioned2009-01-05T14:35:51Z
dc.date.available2009-01-05T14:35:51Z
dc.date.issued2008
dc.identifier.citationSIAM Journal on Optimization. 2008, vol. 19, issue 2, p. 846-862.en
dc.identifier.issn1052-6234
dc.identifier.issn1095-7189
dc.identifier.urihttp://hdl.handle.net/10084/70746
dc.description.abstractA new active set algorithm for minimizing quadratic functions with separable convex constraints is proposed by combining the conjugate gradient method with the projected gradient. It generalizes recently developed algorithms of quadratic programming constrained by simple bounds. A linear convergence rate in terms of the Hessian spectral condition number is proven. Numerical experiments, including the frictional three-dimensional (3D) contact problems of linear elasticity, illustrate the computational performance.en
dc.language.isoenen
dc.publisherSociety for Industrial and Applied Mathematicsen
dc.relation.ispartofseriesSIAM Journal on Optimizationen
dc.relation.urihttps://doi.org/10.1137/060670456en
dc.subjectquadratic functionen
dc.subjectseparable convex constraintsen
dc.subjectactive seten
dc.subjectconjugate gradient methoden
dc.subjectprojected gradienten
dc.subjectconvergence rateen
dc.titleConvergence rate of an optimization algorithm for minimizing quadratic functions with separable convex constraintsen
dc.typearticleen
dc.identifier.locationNení ve fondu ÚKen
dc.identifier.doi10.1137/060670456
dc.identifier.wos000260849600019


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