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无约束优化问题的一种新杂交共轭梯度算法

A New Hybrid Conjugate Gradient Method for Unconstrained Optimization
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摘要 结合DY方法和HS方法给出了求解无约束优化问题的一种新的杂交共轭梯度算法,在无充分下降性假设下,证明了算法在弱Wolfe线搜索条件下的下降性和全局收敛性.数值实验结果表明算法是有效的. A new hybrid conjugate gradient method for unconstrained optimization is presented by combining DY method with HS method in this paper, and the global convergence and descent property of the method are given under the weak Wolfe line search without the hypothesis of sufficient descent. The efficiency of the new method is proved by the numerical result.
出处 《信阳师范学院学报(自然科学版)》 CAS 2009年第2期175-178,共4页 Journal of Xinyang Normal University(Natural Science Edition)
基金 河南省教育厅自然科学基金资助项目(2008110015) 信阳师范学院青年科学基金(20090208)
关键词 无约束优化 杂交共轭梯度算法 WOLFE线搜索 全局收敛性 unconstrained optimization hybrid conjugate gradient method Wolf line search global convergence
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参考文献6

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