Solving nonlinearly constrained global optimization problem via an auxiliary function method

Solving nonlinearly constrained global optimization problem via an auxiliary function method
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通过辅助函数法求解非线性约束全局优化问题

DOI:
10.1016/j.cam.2008.12.017
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发表时间:
2009-08
影响因子:
2.4
通讯作者:
Zhu, Wenxing
Zhu, Wenxing
中科院分区:
数学2区
文献类型:
--
作者:
Ali, M. M.;Zhu, Wenxing

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本文考虑非线性约束的连续全局极小化问题。基于罚函数法的思想,构造了一个辅助函数,该辅助函数具有与原问题大致相同的全局极小值。提出了一种最小化辅助函数的算法,以求出约束全局极小化问题的一个近似约束全局极小值。该算法能摆脱先前收敛的局部极小点,并能以概率1渐近收敛到问题的一个近似全局极小点。数值实验表明,该算法在求解约束全局极小化问题上优于最近一些著名的方法。
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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