Global minimization using an Augmented Lagrangian method with variable lower-level constraints
- BIRGIN, E. G.
- FLOUDAS, C. A.
- MARTINEZ, J. M.
DOIAbstract
A novel global optimization method based on an Augmented Lagrangian framework is introduced for continuous constrained nonlinear optimization problems. At each outer iteration k the method requires the epsilon(k)-global minimization of the Augmented Lagrangian with simple constraints, where epsilon(k) -> epsilon. Global convergence to an epsilon-global minimizer of the original problem is proved. The subproblems are solved using the alpha BB method. Numerical experiments are presented.PRONEX-OptimizationPRONEX-Optimization[PRONEX-CNPq/FAPERJ E-26/171.164/2003-APQ1]FAPESP[06/53768-0 and 06/51827-9]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)CNPq[PROSUL 490333/2004-4]Conselho Nacional de Desenvolvimento Científico e Tecnológi...
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