| 摘要: |
| 基于DL共轭梯度方法,提出了一类修正的DL方法来解决无约束优化问题.该方法相对于DL共轭梯度方法具有一个更好的性质,即在强Wolfe线搜索条件下搜索方向具有充分下降性;证明了该方法在强Wolfe线搜索条件具有全局收敛性. |
| 关键词: 共轭梯度法 强Wolfe线搜索 充分下降性； 全局收敛性 |
| DOI： |
| 分类号: |
| 基金项目: |
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| A Class of Modified DL Conjugate Gradient Method with Sufficient Descent |
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ZHANG Li-lin
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| Abstract: |
| Based on the DL conjugate gradient method, a class of modified DL conjugate gradient method is proposed to solve unconstrained optimization problems. Compared with DL conjugate gradient method, the given method has a better property that search direction possesses the sufficient descent condition under the stonger Wolfe line seach. This paper proves the global convergence of the given method under the stonger Wolfe line seach. |
| Key words: conjugate gradient method stronger Wolfe line seach sufficient descent condition global convergence |
