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

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Author(s):	M. A. Diniz-Ehrhardt ^[1] ; J. M. Martínez ^[2] ; L. G. Pedroso ^[3] Total Authors: 3
Affiliation:	^[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 Total Affiliations: 3
Document type:	Journal article
Source:	COMPUTATIONAL & APPLIED MATHEMATICS; v. 30, n. 1, p. 19-52, 2011-00-00.
Abstract
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)

FAPESP's process:	04/15635-2 - Derivative-free nonlinear programming
Grantee:	Lucas Garcia Pedroso
Support Opportunities:	Scholarships in Brazil - Doctorate


FAPESP's process:	06/53768-0 - Computational methods of optimization
Grantee:	José Mário Martinez Perez
Support Opportunities:	Research Projects - Thematic Grants