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A first-order multigrid method for bound-constrained convex optimization
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SYSNO ASEP 0460326 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title A first-order multigrid method for bound-constrained convex optimization Author(s) Kočvara, Michal (UTIA-B) RID, ORCID
Mohammed, S. (GB)Number of authors 2 Source Title Optimization Methods & Software. - : Taylor & Francis - ISSN 1055-6788
Roč. 31, č. 3 (2016), s. 622-644Number of pages 23 s. Publication form Print - P Language eng - English Country GB - United Kingdom Keywords bound-constrained optimization ; multigrid methods ; linear complementarity problems Subject RIV BA - General Mathematics R&D Projects GAP201/12/0671 GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 UT WOS 000374781100012 EID SCOPUS 84961209711 DOI 10.1080/10556788.2016.1146267 Annotation The aim of this paper is to design an efficient multigrid method for constrained convex optimization problems arising from discretization of some underlying infinite dimensional problems. Due to problem dependency of this approach, we only consider bound constraints with (possibly) a single equality constraint. As our aim is to target large-scale problems, we want to avoid computation of second derivatives of the objective function, thus excluding Newton like methods. We propose a smoothing operator that only uses first-order information and study the computational efficiency of the resulting method. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2017
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