Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/101528
Type: Artigo de evento
Title: A Limited-memory Multipoint Symmetric Secant Method For Bound Constrained Optimization
Author: Burdakov O.P.
Martinez J.M.
Pilotta E.A.
Abstract: A new algorithm for solving smooth large-scale minimization problems with bound constraints is introduced. The way of dealing with active constraints is similar to the one used in some recently introduced quadratic solvers. A limited-memory multipoint symmetric secant method for approximating the Hessian is presented. Positive-definiteness of the Hessian approximation is not enforced. A combination of trust-region and conjugate-gradient approaches is used to explore a useful negative curvature information. Global convergence is proved for a general model algorithm. Results of numerical experiments are presented.
Editor: 
Rights: fechado
Identifier DOI: 10.1023/A:1021561204463
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-1642543147&partnerID=40&md5=25eae5f0516204dd71cc3371243f1c33
Date Issue: 2002
Appears in Collections:Unicamp - Artigos e Outros Documentos

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