Artículos de revistas
A Gauss-Newton Approach for Solving Constrained Optimization Problems Using Differentiable Exact Penalties
Registro en:
Journal Of Optimization Theory And Applications. Springer/plenum Publishers, v. 156, n. 2, n. 417, n. 449, 2013.
0022-3239
WOS:000315293500013
10.1007/s10957-012-0114-6
Autor
Andreani, R
Fukuda, EH
Silva, PJS
Institución
Resumen
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) We propose a Gauss-Newton-type method for nonlinear constrained optimization using the exact penalty introduced recently by Andre and Silva for variational inequalities. We extend their penalty function to both equality and inequality constraints using a weak regularity assumption, and as a result, we obtain a continuously differentiable exact penalty function and a new reformulation of the KKT conditions as a system of equations. Such reformulation allows the use of a semismooth Newton method, so that local superlinear convergence rate can be proved under an assumption weaker than the usual strong second-order sufficient condition and without requiring strict complementarity. Besides, we note that the exact penalty function can be used to globalize the method. We conclude with some numerical experiments using the collection of test problems CUTE. 156 2 417 449 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) CNPq [PRONEX-CNPq/FAPERJ E-26/171.510/2006-APQ1] FAPESP [2010/20572-0, 2007/53471-0, 2006/53768-0, 2005/02163-8] CNPq [303030/2007-0, 474138/2008-9]