Artículos de revistas
Derivative-free methods for nonlinear programming with general lower-level constraints
Registro en:
Computational & Applied Mathematics. Soc Brasileira Matematica Aplicada & Computacional, v. 30, n. 1, n. 19, n. 52, 2011.
0101-8205
WOS:000288862400003
Autor
Diniz-Ehrhardt, MA
Martinez, JM
Pedroso, LG
Institución
Resumen
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Augmented Lagrangian methods for derivative-free continuous optimization with constraints are introduced in this paper. The algorithms inherit the convergence results obtained by Andreani, Birgin, Martinez and Schuverdt for the case in which analytic derivatives exist and are available. In particular, feasible limit points satisfy KKT conditions under the Constant Positive Linear Dependence (CPLD) constraint qualification. The form of our main algorithm allows us to employ well established derivative-free subalgorithms for solving lower-level constrained subproblems. Numerical experiments are presented. 30 1 19 52 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 [2006/53768-0, 2004/15635-2]