. . . "quadratic programming; rate of convergence; bound constraints"@en . "Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities" . "[0B01E55CB5D9]" . "978-80-87136-00-3" . . "RIV/61989100:27240/07:00014979!RIV08-AV0-27240___" . "P\u0159edpodm\u00EDn\u011Bn\u00ED \u00FAloh kvadratick\u00E9ho programov\u00E1n\u00ED"@cs . "Dost\u00E1l, Zden\u011Bk" . . "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"@en . . "\u00DAstav informatiky AV \u010CR" . . "RIV/61989100:27240/07:00014979" . . "2"^^ . . "1"^^ . "Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities"@en . "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" . . . "P(1ET400300415), P(GA201/07/0294), Z(MSM6198910027)" . . . "27240" . . . "Praha" . . "Computation Methods with Applications" . "Domor\u00E1dov\u00E1, Marta" . . "V prezentaci ukazujeme p\u0159edpodm\u00EDn\u011Bn\u00ED algoritmu MPRGP s c\u00EDlem zlep\u0161it rychlost konvergence. P\u0159edpodm\u00EDn\u011Bn\u00ED zasahuje v\u0161echny kroky algoritmu, tedy i ty neline\u00E1rn\u00ED."@cs . "Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities"@en . "Preconditioning for bound constrained quadratic programming problems arising from discretization of variational inequalities" . "P\u0159edpodm\u00EDn\u011Bn\u00ED \u00FAloh kvadratick\u00E9ho programov\u00E1n\u00ED"@cs . . "443519" . "22-22" . "1"^^ .