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An Algorithm for Rn Constrained Global Optimization Based on Filled Function Method

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2 Author(s)
Weixiang Wang ; Shanghai Second Polytech. Univ., Shanghai ; Youlin Shang

Many aspects in the study of the development and the use of advanced information technologies and systems involves constrained global optimization. In this paper, a filled function with one parameter is proposed for escaping the current local minimizer. Then a new algorithm for obtaining a global optimizer is presented. Using this method, a global minimizer can be obtained just by searching for local optimizers of the original problem and some certain unconstrained optimization problems. The numerical results show the efficiency of this method.

Published in:

Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on

Date of Conference:

23-24 Jan. 2008

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