| 一类全局收敛的记忆梯度法及其线性收敛性 |
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| 引用本文： | 汤京永,时贞军. 一类全局收敛的记忆梯度法及其线性收敛性[J]. 数学进展, 2007, 36(1): 67-75 |
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| 作者姓名： | 汤京永 时贞军 |
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| 作者单位： | 1. 信阳师范学院数学与信息科学学院,信阳,河南,464000
2. 曲阜师范大学运筹与管理学院,日照,山东,276826 |
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| 摘 要： | 本文研究一类新的解无约束最优化问题的记忆梯度法,在强Wolfe线性搜索下证明了其全局收敛性．当目标函数为一致凸函数时,对其线性收敛速率进行了分析．数值试验表明算法是很有效的．
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| 关 键 词： | 无约束最优化 记忆梯度法 强Wolfe线性搜索 线性收敛速率 |
| 文章编号： | 1000-0917（2007）01-0067-09 |
| 收稿时间： | 2004-06-14 |
| 修稿时间： | 2005-05-20 |
A Class of Global Convergent Memory Gradient Methods and Its Linear Convergence Rate |
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| TANG Jingyong,SHI Zhenjun. A Class of Global Convergent Memory Gradient Methods and Its Linear Convergence Rate[J]. Advances in Mathematics(China), 2007, 36(1): 67-75 |
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| Authors: | TANG Jingyong SHI Zhenjun |
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| Affiliation: | College of Operations Research and Management, Qufu Normal University, Rizhao, Shandong, 276826, P. R. China |
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| Abstract: | In this paper,a new class of memory gradient methods for unconstrained optimization problem is presented.The convergence of the algorithms with strong Wolfe line search is proved.The linear convergence rate is investigated when the objective function is uniformly convex.Numberical experiments show that the new algorithm is very effcient. |
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| Keywords: | unconstrained optimization problem memory gradient method strong Wolfe line search linear convergence rate |
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