| 非精确线搜索下一类新的混合共轭梯度法研究 |
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| 引用本文： | 孟姗姗,熊丽涢,廖月红.非精确线搜索下一类新的混合共轭梯度法研究[J].河池师专学报,2011(2):1-4. |
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| 作者姓名： | 孟姗姗 熊丽涢 廖月红 |
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| 作者单位： | 重庆师范大学数学学院,重庆400047 |
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| 基金项目： | 国家自然科学基金资助项目（10971241）. |
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| 摘 要： | 共轭梯度法在求解无约束最优化问题中起着重要作用。通过构造一个新的参数βk^＊，并与βk^DY结合，得到了一类新的混合迭代参数，此类混合共轭梯度法在迭代过程中保持下降性；在非精确强wolf线搜索下此算法具有全局收敛性。
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| 关 键 词： | 无约束最优化 混合共轭梯度法 强wolf线搜索 全局收敛性 |
Inexact Line Search for the Next Class of New Mixed Conjugate Gradient Method |
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| MENG Shan-shan,XIONG Li-yun,LIAO Yue-hong.Inexact Line Search for the Next Class of New Mixed Conjugate Gradient Method[J].Journal of Hechi Normal College,2011(2):1-4. |
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| Authors: | MENG Shan-shan XIONG Li-yun LIAO Yue-hong |
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| Institution: | ( Department of Mathematics, Chongqing Normal University, Chongqing 400047, China) |
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| Abstract: | Conjugate gradient method plays an important role in solving unconstrained optimization problems. By constructing a new parameter,βk^＊and combining it with βk^DY, a new class of mixed iteration parameters are obtained. Such hybrid conjugate gradient method maintains descent in the iterative process, and this algorithm possesses global convergence under the condition of the strong wolf inexact line search. |
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| Keywords: | unconstrained optimization hybrid conjugate gradient strong wolf line search global convergence |
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