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Solving nonlinearly constrained global optimization problem via an auxiliary function method

✍ Scribed by Wenxing Zhu; M.M. Ali

Publisher: Elsevier Science
Year: 2009
Tongue: English
Weight: 752 KB
Volume: 230
Category: Article
ISSN: 0377-0427
DOI: 10.1016/j.cam.2008.12.017

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✦ Synopsis

This paper considers the nonlinearly constrained continuous global minimization problem. Based on the idea of the penalty function method, an auxiliary function, which has approximately the same global minimizers as the original problem, is constructed. An algorithm is developed to minimize the auxiliary function to find an approximate constrained global minimizer of the constrained global minimization problem. The algorithm can escape from the previously converged local minimizers, and can converge to an approximate global minimizer of the problem asymptotically with probability one. Numerical experiments show that it is better than some other well known recent methods for constrained global minimization problems.

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