SUBSPACE TRUST-REGION ALGORITHM WITH CONIC MODEL FOR UNCONSTRAINED OPTIMIZATION

被引:3
|
作者
Zhang, Xin [1 ]
Wen, Jie [2 ]
Ni, Qin [2 ]
机构
[1] Nanjing Univ, Jinling Coll, Nanjing 210089, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Nanjing 210016, Peoples R China
来源
关键词
Unconstrained optimization; conic model; subspace method; trust region method; global convergence;
D O I
10.3934/naco.2013.3.223
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
SUBSPACE In this paper, a new subspace algorithm is proposed for unconstrained optimization. In this new algorithm, the subspace technique is used in the trust region subproblem with conic model, and the dogleg method is modified to solve this subproblem. The global convergence of this algorithm under some reasonable conditions is established. Numerical experiment shows that this algorithm may be superior to the corresponding algorithm without using subspace technique especially for large scale problems.
引用
收藏
页码:223 / 234
页数:12
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