Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/68711
Type: Artigo
Title: On the maximization of a concave quadratic function with box constraints
Author: Friedlander, Ana
Martínez, José Mario
Abstract: A new method for maximizing a concave quadratic function with bounds on the variables is introduced. The new algorithm combines conjugate gradients with gradient projection techniques, as the algorithm of More and Toraldo [SIAM J. Optimization, 1 (1991), pp, 93-113] and other well-known methods do. A new strategy for the decision of leaving the current face is introduced that makes it possible to obtain finite convergence even for a singular Hessian and in the presence of dual degeneracy. Numerical experiments are presented.
A new method for maximizing a concave quadratic function with bounds on the variables is introduced. The new algorithm combines conjugate gradients with gradient projection techniques, as the algorithm of More and Toraldo [SIAM J. Optimization, 1 (1991),
Subject: Programação quadrática
Métodos do gradiente conjugado
Country: Estados Unidos
Editor: Society for Industrial and Applied Mathematics
Citation: Siam Journal On Optimization. Siam Publications, v. 4, n. 1, n. 177, n. 192, 1994.
Rights: fechado
Identifier DOI: 10.1137/0804010
Address: https://epubs.siam.org/doi/abs/10.1137/0804010
Date Issue: 1994
Appears in Collections:IMECC - Artigos e Outros Documentos

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