Superlinearly convergent trust-region method without the assumption of positive-definite Hessian
文献类型:期刊论文
作者 | Zhang, J. L.; Wang, Y.![]() ![]() |
刊名 | JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
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出版日期 | 2006-04-01 |
卷号 | 129期号:1页码:201-218 |
关键词 | trust-region methods trust-region radius global convergence superlinear convergence local error bound |
ISSN号 | 0022-3239 |
DOI | 10.1007/s10957-006-9053-4 |
英文摘要 | In this paper, we reinvestigate the trust-region method by reformulating its subproblem: the trust-region radius is guided by gradient information at the current iteration and is self-adaptively adjusted. A trust-region algorithm based on the proposed subproblem is proved to be globally convergent. Moreover, the superlinear convergence of the new algorithm is shown without the condition that the Hessian of the objective function at the solution be positive definite. Preliminary numerical results indicate that the performance of the new method is notable. |
WOS研究方向 | Operations Research & Management Science ; Mathematics |
语种 | 英语 |
WOS记录号 | WOS:000242660000012 |
出版者 | SPRINGER/PLENUM PUBLISHERS |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/3443] ![]() |
专题 | 应用数学研究所 |
通讯作者 | Zhang, J. L. |
作者单位 | 1.Grad Univ, Sch Management, Chinese Acad Sci, Res Ctr Data Tech & Knowledge Econ, Beijing, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, J. L.,Wang, Y.,Zhang, X. S.. Superlinearly convergent trust-region method without the assumption of positive-definite Hessian[J]. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS,2006,129(1):201-218. |
APA | Zhang, J. L.,Wang, Y.,&Zhang, X. S..(2006).Superlinearly convergent trust-region method without the assumption of positive-definite Hessian.JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS,129(1),201-218. |
MLA | Zhang, J. L.,et al."Superlinearly convergent trust-region method without the assumption of positive-definite Hessian".JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 129.1(2006):201-218. |
入库方式: OAI收割
来源:数学与系统科学研究院
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