吉林大学学报(理学版) ›› 2022, Vol. 60 ›› Issue (2): 247-252.

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几种混合型共轭梯度法的数值性能

黄元元, 杨颖珂   

  1. 河南科技大学 数学与统计学院, 河南 洛阳 471023
  • 收稿日期:2021-06-12 出版日期:2022-03-26 发布日期:2022-03-26
  • 通讯作者: 黄元元 E-mail:yyuanhuang@126.com

Numerical Performance of Several Hybrid Conjugate Gradient Methods

HUANG Yuanyuan, YANG Yingke   

  1. School of Mathematics and Statistics, Henan University of Science & Technology, Luoyang 471023, Henan Province, China
  • Received:2021-06-12 Online:2022-03-26 Published:2022-03-26

摘要: 考虑几种混合型的共轭梯度法, 采用弱Wolfe线搜索确定步长, 利用正交化策略产生满足充分下降条件的下降方向, 通过CUTEst测试问题验证这些算法的有效性, 并分析这些算法的数值性能.

关键词: 无约束优化, 混合型共轭梯度法, 充分下降条件, 数值分析

Abstract: We considered several hybrid conjugate gradient methods, determined their step length by weak Wolfe line search, and generated the descent direction satisfying the sufficient descent condition by orthogonalization strategy. The effectiveness of these algorithms was verified by CUTEst test problems, and the numerical performance of these algorithms was analyzed.

Key words: unconstrained optimization, hybrid conjugate gradient method, sufficient descent condition, numerical analysis

中图分类号: 

  • O224