Superlinearly convergent trust-region method without the assumption of positive-definite Hessian

doi:10.1007/s10957-006-9053-4

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	Superlinearly convergent trust-region method without the assumption of positive-definite Hessian
	Zhang, J. L.; Wang, Y.; Zhang, X. S.
	2006-04-01
发表期刊	JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
ISSN	0022-3239
卷号	129 期号:1 页码:201-218
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.
关键词	trust-region methods trust-region radius global convergence superlinear convergence local error bound
DOI	10.1007/s10957-006-9053-4
语种	英语
WOS研究方向	Operations Research & Management Science ; Mathematics
WOS类目	Operations Research & Management Science ; Mathematics, Applied
WOS记录号	WOS:000242660000012
出版者	SPRINGER/PLENUM PUBLISHERS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/3444
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.