Convergence property and modifications of a memory gradient method

被引：1

作者：

Shi, ZJ ^{[1
]}

Shen, J

机构：

[1] Qufu Normal Univ, Coll Operat Res & Management, Shandong 276826, Peoples R China

[2] Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, Beijing 100080, Peoples R China

[3] Univ Michigan, Dept Comp & Informat Sci, Dearborn, MI 48128 USA

来源：

ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH | 2005年 / 22卷 / 04期

基金：

美国国家科学基金会;

关键词：

unconstrained optimization; memory gradient method; exact line search; convergence;

D O I：

10.1142/S0217595905000625

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：

We study properties of a modified memory gradient method, including the global convergence and rate of convergence. Numerical results show that modified memory gradient methods are effective in solving large-scale minimization problems.

引用

页码：463 / 477

页数：15

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