Outer Trust-Region Method for Constrained Optimization
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
---|---|
Data(s) |
20/10/2012
20/10/2012
2011
|
Resumo |
Given an algorithm A for solving some mathematical problem based on the iterative solution of simpler subproblems, an outer trust-region (OTR) modification of A is the result of adding a trust-region constraint to each subproblem. The trust-region size is adaptively updated according to the behavior of crucial variables. The new subproblems should not be more complex than the original ones, and the convergence properties of the OTR algorithm should be the same as those of Algorithm A. In the present work, the OTR approach is exploited in connection with the ""greediness phenomenon"" of nonlinear programming. Convergence results for an OTR version of an augmented Lagrangian method for nonconvex constrained optimization are proved, and numerical experiments are presented. PRONEX-CNPq/FAPERJ[E-26/111.449/2010-APQ1] PRONEX-CNPq/FAPERJ FAPESP[2006/53768-0] Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) FAPESP[2005/57684-2] Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) CNPq |
Identificador |
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, v.150, n.1, p.142-155, 2011 0022-3239 http://producao.usp.br/handle/BDPI/30378 10.1007/s10957-011-9815-5 |
Idioma(s) |
eng |
Publicador |
SPRINGER/PLENUM PUBLISHERS |
Relação |
Journal of Optimization Theory and Applications |
Direitos |
restrictedAccess Copyright SPRINGER/PLENUM PUBLISHERS |
Palavras-Chave | #Nonlinear programming #Augmented Lagrangian method #Trust regions #Operations Research & Management Science #Mathematics, Applied |
Tipo |
article original article publishedVersion |