基于填充函数法的Rn约束全局优化算法

First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008) Pub Date : 2008-01-23 DOI:10.1109/WKDD.2008.123

Wei-xiang Wang, Y. Shang

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引用次数: 2

摘要

在研究开发和使用先进的信息技术和系统的许多方面涉及约束全局优化。本文提出了一个带一个参数的填充函数来转义当前的局部最小值。在此基础上，提出了一种求全局优化器的新算法。利用该方法，只需搜索原问题和某些无约束优化问题的局部优化器，即可得到全局最优解。数值结果表明了该方法的有效性。

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

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.

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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)

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