Název:
A Generalized Limited-Memory BNS Method Based on the Block BFGS Update
Autoři:
Vlček, Jan ; Lukšan, Ladislav Typ dokumentu: Příspěvky z konference Konference/Akce: Programs and Algorithms of Numerical Mathematics /18./, Janov nad Nisou (CZ), 20160619
Rok:
2017
Jazyk:
eng
Abstrakt: A block version of the BFGS variable metric update formula is investigated. It satisfies the quasi-Newton conditions with all used difference vectors and gives the best improvement of convergence in some sense for quadratic objective functions, but it does not guarantee that the direction vectors are descent for general functions. To overcome this difficulty and utilize the advantageous properties of the block BFGS update, a block version of the limited-memory BNS method for large scale unconstrained optimization is proposed. The algorithm is globally convergent for convex sufficiently smooth functions and our numerical experiments indicate its efficiency.
Klíčová slova:
block variable metric methods; global convergence; limited-memory methods; numerical results; the BFGS update; unconstrained minimization Číslo projektu: GA13-06684S (CEP) Poskytovatel projektu: GA ČR Zdrojový dokument: Programs and algorithms of numerical mathematics 18, ISBN 978-80-85823-67-7 Poznámka: Související webová stránka: http://dml.cz/handle/10338.dmlcz/703010
Instituce: Ústav informatiky AV ČR
(web)
Informace o dostupnosti dokumentu:
Dokument je dostupný v repozitáři Akademie věd. Původní záznam: http://hdl.handle.net/11104/0272937