A first-order multigrid method for bound-constrained convex optimization

0460326 - ÚTIA 2017 RIV GB eng J - Článek v odborném periodiku
Kočvara, Michal - Mohammed, S.
A first-order multigrid method for bound-constrained convex optimization.
Optimization Methods & Software. Roč. 31, č. 3 (2016), s. 622-644. ISSN 1055-6788. E-ISSN 1029-4937
Grant CEP: GA ČR(CZ) GAP201/12/0671
Grant ostatní: European Commission - EC(XE) 313781
Institucionální podpora: RVO:67985556
Klíčová slova: bound-constrained optimization * multigrid methods * linear complementarity problems
Kód oboru RIV: BA - Obecná matematika
Impakt faktor: 1.023, rok: 2016
http://library.utia.cas.cz/separaty/2016/MTR/kocvara-0460326.pdf

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.
Trvalý link: http://hdl.handle.net/11104/0261898