A Comparative Study of Three New Conjugate Gradient Methods with Exact Line Search

被引：0

作者：

Hamoda, Mohamed ^{[1
]}

Rivaie, Mohd ^{[2
]}

Abshar, Abdelrhaman ^{[1
]}

Mamat, Mustafa ^{[3
]}

机构：

[1] Univ Malaysia Terengganu, Sch Informat & Appl Math, Terengganu 21030, Malaysia

[2] Univ Teknol MARA, Dept Comp Sci & Math, Terengganu 23000, Malaysia

[3] Univ Sultan Zainal Abidin, Fac Informat & Comp, Dept Computat & Appl Math, Terengganu 22200, Malaysia

来源：

22ND NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM22) | 2015年 / 1682卷

关键词：

Conjugate gradient method; exact line search; global convergence; large scale; unconstrained optimization; GLOBAL CONVERGENCE PROPERTIES; OPTIMIZATION; MINIMIZATION;

D O I：

10.1063/1.4932439

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Conjugate Gradient methods play an important role in solving unconstrained optimization, especially for large scale problems. In this paper, we compared the performance profile of the classical conjugate gradient coefficients FR, PRP with three new beta(k). These three new beta(k) possess global convergence properties using the exact line search. Preliminary numerical results show that the three new beta(k) are very promising and efficient when compared to CG coefficients IA.PRP.

引用

页数：6

共 18 条

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