New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization
文献类型：期刊论文
| 作者 | Zhao, Ting1; Liu, Hongwei1; Liu, Zexian2,3 |
| 刊名 | NUMERICAL ALGORITHMS
 |
| 出版日期 | 2020-10-28 |
| 页码 | 34 |
| 关键词 | Conjugate gradient method p-regularization model Subspace technique Nonmonotone line search Unconstrained optimization |
| ISSN号 | 1017-1398 |
| DOI | 10.1007/s11075-020-01017-1 |
| 英文摘要 | In this paper, two new subspace minimization conjugate gradient methods based on p-regularization models are proposed, where a special scaled norm in p-regularization model is analyzed. Different choices of special scaled norm lead to different solutions to the p-regularized subproblem. Based on the analyses of the solutions in a two-dimensional subspace, we derive new directions satisfying the sufficient descent condition. With a modified nonmonotone line search, we establish the global convergence of the proposed methods under mild assumptions. R-linear convergence of the proposed methods is also analyzed. Numerical results show that, for the CUTEr library, the proposed methods are superior to four conjugate gradient methods, which were proposed by Hager and Zhang (SIAM J. Optim. 16(1):170-192, 2005), Dai and Kou (SIAM J. Optim. 23(1):296-320, 2013), Liu and Liu (J. Optim. Theory. Appl. 180(3):879-906, 2019) and Li et al. (Comput. Appl. Math. 38(1):2019), respectively. |
| 资助项目 | National Science Foundation of China[11901561] ; Guangxi Natural Science Foundation[2018GXNSFBA281180] ; China Postdoctoral Science Foundation[2019M660833] |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000582812700002 |
| 出版者 | SPRINGER |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/52394]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Liu, Hongwei |
| 作者单位 | 1.Xidian Univ, Sch Math & Stat, Xian 710126, Peoples R China 2.Chinese Acad Sci, State Key Lab Sci & Engn Comp, Inst Computat Math & Sci Engn Comp, AMSS, Beijing 100190, Peoples R China 3.Guizhou Univ, Sch Math & Stat, Guiyang 550025, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Ting,Liu, Hongwei,Liu, Zexian. New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization[J]. NUMERICAL ALGORITHMS,2020:34. |
| APA | Zhao, Ting,Liu, Hongwei,&Liu, Zexian.(2020).New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization.NUMERICAL ALGORITHMS,34. |
| MLA | Zhao, Ting,et al."New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization".NUMERICAL ALGORITHMS (2020):34. |
入库方式： OAI收割
来源：数学与系统科学研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。