A new alternating direction trust region method based on conic model for solving unconstrained optimization

被引：2
|
作者：
Zhu, Honglan [1 ,2 ,3 ]
Ni, Qin [1 ]
Jiang, Jianlin [1 ]
Dang, Chuangyin [3 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Dept Math, Nanjing, Peoples R China
[2] Huaiyin Inst Technol, Business Sch, Huaian, Peoples R China
[3] City Univ Hong Kong, Dept Syst Engn & Engn Management, Kowloon, Hong Kong, Peoples R China
来源：
OPTIMIZATION | 2021年 / 70卷 / 07期
基金：
中国国家自然科学基金;
关键词：
Unconstrained optimization; conic model; trust region method; alternating direction search method; global convergence; OPTIMALITY CONDITIONS; ALGORITHM; MINIMIZATION;
D O I：
10.1080/02331934.2020.1745793
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
In this paper, a new alternating direction trust region method based on conic model is used to solve unconstrained optimization problems. By use of the alternating direction search method, the new conic model trust region subproblem is solved by two steps in two orthogonal directions. This new idea overcomes the shortcomings of conic model subproblem which is difficult to solve. Then the global convergence of the method under some reasonable conditions is established. Numerical experiment shows that this method may be better than the dogleg method to solve the subproblem, especially for large-scale problems.
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页码：1555 / 1579
页数：25
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