An efficient nonmonotone adaptive cubic regularization method with line search for unconstrained optimization problem

被引：5

作者：

Li, Qun ^{[1
]}

Zheng, Bing ^{[1
]}

Zheng, Yutao ^{[1
]}

机构：

[1] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Gansu, Peoples R China

来源：

APPLIED MATHEMATICS LETTERS | 2019年 / 98卷

基金：

中国国家自然科学基金;

关键词：

Unconstrained optimization; Adaptive cubic regularization method; Nonmonotone line search; Barzilai-Borwein gradient method; BORWEIN GRADIENT-METHOD; TRUST-REGION METHOD; BARZILAI;

D O I：

10.1016/j.aml.2019.05.040

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we present an efficient nonmonotone adaptive cubic regularization method with line search for solving large-scale unconstrained optimization problem. Its global convergence is analyzed. Numerical experiments are performed to show the efficiency and effectiveness of the proposed method and its superiority to the other existing methods. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页码：74 / 80

页数：7

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