Derivative-free methods for nonlinear programming with general lower-level constraints

Autor(es)

M. A. Diniz-Ehrhardt ^[1] ; J. M. Martínez ^[2] ; L. G. Pedroso ^[3]

Afiliação do(s) autor(es)

^[1] University of Campinas. IMECC. Department of Applied Mathematics - Brasil

^[2] University of Campinas. IMECC. Department of Applied Mathematics - Brasil

^[3] Federal University of Paraná. Department of Mathematics - Brasil

• Tipo de documento: Artigo Científico
• Fonte: COMPUTATIONAL & APPLIED MATHEMATICS; v. 30, n. 1, p. 19-52, 2011-00-00.

Resumo

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, Martínez 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. (AU)

• Processo FAPESP: 04/15635-2 - Programação não-linear sem derivadas
• Beneficiário: Lucas Garcia Pedroso
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 06/53768-0 - Métodos computacionais de otimização
• Beneficiário: José Mário Martinez Perez
• Modalidade de apoio: Auxílio à Pesquisa - Temático