anaugmentedlagrangiantrustregionmethodwithabiobjectstrategy

	anaugmentedlagrangiantrustregionmethodwithabiobjectstrategy
	Kou Caixia 1; Chen Zhongwen 2; Dai Yuhong3 ; Han Haifei 4
	2018
发表期刊	journalofcomputationalmathematics
ISSN	0254-9409
卷号	36 期号:3 页码:331
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.
语种	英语
资助项目	[Chinese NSF] ; [National 973 Program of China]
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/42322
专题	计算数学与科学工程计算研究所
作者单位	1.北京邮电大学 2.School of Mathematical Sciences,Soochow University 3.中国科学院数学与系统科学研究院 4.苏州大学
推荐引用方式 GB/T 7714	Kou Caixia,Chen Zhongwen,Dai Yuhong,et al. anaugmentedlagrangiantrustregionmethodwithabiobjectstrategy[J]. journalofcomputationalmathematics,2018,36(3):331.
APA	Kou Caixia,Chen Zhongwen,Dai Yuhong,&Han Haifei.(2018).anaugmentedlagrangiantrustregionmethodwithabiobjectstrategy.journalofcomputationalmathematics,36(3),331.
MLA	Kou Caixia,et al."anaugmentedlagrangiantrustregionmethodwithabiobjectstrategy".journalofcomputationalmathematics 36.3(2018):331.