Minimizing quadratic functions with semidefinite Hessian subject to bound constraints

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F15%3A86097140" target="_blank" >RIV/61989100:27740/15:86097140 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.camwa.2015.08.015" target="_blank" >http://dx.doi.org/10.1016/j.camwa.2015.08.015</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.camwa.2015.08.015" target="_blank" >10.1016/j.camwa.2015.08.015</a>

Result language
angličtina
Original language name
Minimizing quadratic functions with semidefinite Hessian subject to bound constraints
Original language description
he MPRGP (modified proportioning with reduced gradient projections) algorithm for minimization of the strictly convex quadratic function subject to bound constraints is adapted to the solution of problems with a semidefinite Hessian A. The adapted algorithm accepts the decrease directions that belong to the null space of A and generates the iterates that are proved to minimize the cost function. The paper examines specific features of the solution of the problems with convex, but not necessarily strictly convex Hessian. The performance of the algorithm is demonstrated by the solution of a semi-coercive contact problem of elasticity and a 3D particle dynamics problem. The results are compared with those obtained by the spectral projected gradient methodand the projected-Jacobi method.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)