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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Global minimization using an Augmented Lagrangian method with variable lower-level constraints

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Author(s):
Birgin, E. G. [1] ; Floudas, C. A. [2] ; Martinez, J. M. [3]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, IME, Dept Comp Sci, BR-05508090 Sao Paulo - Brazil
[2] Princeton Univ, Dept Chem Engn, Princeton, NJ 08544 - USA
[3] Univ Estadual Campinas, Dept Appl Math, IMECC, BR-13081970 Campinas, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: MATHEMATICAL PROGRAMMING; v. 125, n. 1, p. 139-162, SEP 2010.
Web of Science Citations: 74
Abstract

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. (AU)

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