A new simple model trust-region method with generalized Barzilai-Borwein parameter for large-scale optimization

被引：0

作者：

ZHOU QunYan ^{[1
]}

SUN WenYu ^{[2
]}

ZHANG HongChao ^{[3
]}

机构：

[1] School of Mathematics and Physics, Jiangsu University of Technology

[2] School of Mathematical Sciences, Jiangsu Key Laboratory for NSLSCS,Nanjing Normal University

[3] Department of Mathematics, Louisiana State University

来源：

ScienceChina(Mathematics) | 2016年 / 59卷 / 11期

基金：

中国国家自然科学基金; 美国国家科学基金会;

关键词：

unconstrained optimization; Barzilai-Borwein method; weak quasi-Newton equation; trust region method; global convergence;

D O I：

暂无

中图分类号：

O224 [最优化的数学理论];

学科分类号：

070105 ; 1201 ;

摘要：

In this paper, a new trust region method with simple model for solving large-scale unconstrained nonlinear optimization is proposed. By employing the generalized weak quasi-Newton equations, we derive several schemes to construct variants of scalar matrices as the Hessian approximation used in the trust region subproblem. Under some reasonable conditions, global convergence of the proposed algorithm is established in the trust region framework. The numerical experiments on solving the test problems with dimensions from 50 to 20,000 in the CUTEr library are reported to show efficiency of the algorithm.

引用

页码：2265 / 2280

页数：16

共 22 条

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