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A first-order multigrid method for bound-constrained convex optimization
- 1.0460326 - ÚTIA 2017 RIV GB eng J - Journal Article
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
R&D Projects: GA ČR(CZ) GAP201/12/0671
Grant - others:European Commission - EC(XE) 313781
Institutional support: RVO:67985556
Keywords : bound-constrained optimization * multigrid methods * linear complementarity problems
Subject RIV: BA - General Mathematics
Impact factor: 1.023, year: 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.
Permanent Link: http://hdl.handle.net/11104/0261898
Number of the records: 1