AN AUGMENTED LAGRANGIAN TRUST REGION METHOD WITH A BI-OBJECT STRATEGY

doi:10.4208/jcm.1705-m2016-0820

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 计算数学与科学工程计算研究所

	AN AUGMENTED LAGRANGIAN TRUST REGION METHOD WITH A BI-OBJECT STRATEGY
	Kou, Caixia 1; Chen, Zhongwen 2; Dai, Yu-Hong3 ; Han, Haifei 2
刊名	JOURNAL OF COMPUTATIONAL MATHEMATICS
	2018
卷号	36 期号:3 页码:331-350
关键词	Nonlinear constrained optimization Augmented Lagrangian function Bi-object strategy Global convergence
ISSN号	0254-9409
DOI	10.4208/jcm.1705-m2016-0820
英文摘要	An augmented Lagrangian trust region method with a bi-object strategy is proposed for solving nonlinear equality constrained optimization, which falls in between penalty-type methods and penalty-free ones. At each iteration, a trial step is computed by minimizing a quadratic approximation model to the augmented Lagrangian function within a trust region. The model is a standard trust region subproblem for unconstrained optimization and hence can efficiently be solved by many existing methods. To choose the penalty parameter, an auxiliary trust region subproblem is introduced related to the constraint violation. It turns out that the penalty parameter need not be monotonically increasing and will not tend to infinity. A bi-object strategy, which is related to the objective function and the measure of constraint violation, is utilized to decide whether the trial step will be accepted or not. Global convergence of the method is established under mild assumptions. Numerical experiments are made, which illustrate the efficiency of the algorithm on various difficult situations.
资助项目	Chinese NSF[11631013] ; Chinese NSF[11331012] ; Chinese NSF[71331001] ; Chinese NSF[11401038] ; Chinese NSF[11471052] ; Chinese NSF[11371273] ; National 973 Program of China[2015CB856000]
WOS研究方向	Mathematics
语种	英语
出版者	GLOBAL SCIENCE PRESS
WOS记录号	WOS:000455995700002
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/32256]
专题	计算数学与科学工程计算研究所
通讯作者	Kou, Caixia
作者单位	1.Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China 2.Soochow Univ, Sch Math Sci, Suzhou 215006, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, ICMSEC, LSEC, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Kou, Caixia,Chen, Zhongwen,Dai, Yu-Hong,et al. AN AUGMENTED LAGRANGIAN TRUST REGION METHOD WITH A BI-OBJECT STRATEGY[J]. JOURNAL OF COMPUTATIONAL MATHEMATICS,2018,36(3):331-350.
APA	Kou, Caixia,Chen, Zhongwen,Dai, Yu-Hong,&Han, Haifei.(2018).AN AUGMENTED LAGRANGIAN TRUST REGION METHOD WITH A BI-OBJECT STRATEGY.JOURNAL OF COMPUTATIONAL MATHEMATICS,36(3),331-350.
MLA	Kou, Caixia,et al."AN AUGMENTED LAGRANGIAN TRUST REGION METHOD WITH A BI-OBJECT STRATEGY".JOURNAL OF COMPUTATIONAL MATHEMATICS 36.3(2018):331-350.