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A Modified Limited-Memory BNS Method for Unconstrained Minimization Based on the Conjugate Directions Idea
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SYSNO ASEP 0442775 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název A Modified Limited-Memory BNS Method for Unconstrained Minimization Based on the Conjugate Directions Idea Tvůrce(i) Vlček, Jan (UIVT-O) SAI, RID, ORCID
Lukšan, Ladislav (UIVT-O) SAI, RIDZdroj.dok. Optimization Methods & Software. - : Taylor & Francis - ISSN 1055-6788
Roč. 30, č. 3 (2015), s. 616-633Poč.str. 18 s. Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova unconstrained minimization ; variable metric methods ; limited-memory methods ; the BFGS update ; conjugate directions ; numerical results Vědní obor RIV BA - Obecná matematika CEP GA13-06684S GA ČR - Grantová agentura ČR Institucionální podpora UIVT-O - RVO:67985807 UT WOS 000356936400011 EID SCOPUS 84933672462 DOI 10.1080/10556788.2014.955101 Anotace A modification of the limited-memory variable metric BNS method for large-scale unconstrained optimization is proposed, which consists in corrections (derived from the idea of conjugate directions) of the used difference vectors for better satisfaction of the previous quasi-Newton (QN) conditions. In comparison with [Vlček and Lukšan, A conjugate directions approach to improve the limited-memory BFGS method, Appl. Math. Comput. 219 (2012), pp. 800–809], where a similar approach is used, correction vectors from more previous iterations can be applied here. For quadratic objective functions, the improvement of convergence is the best one in some sense, all stored corrected difference vectors are conjugate and the QN conditions with these vectors are satisfied. Global convergence of the algorithm is established for convex sufficiently smooth functions. Numerical experiments demonstrate the efficiency of the new method. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2016
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