Some new three-term Hestenes-Stiefel conjugate gradient methods with affine combination

被引:20
|
作者
Dong, Xiao-Liang [1 ,2 ]
Han, De-Ren [1 ]
Ghanbari, Reza [3 ]
Li, Xiang-Li [4 ]
Dai, Zhi-Feng [5 ]
机构
[1] Nanjing Normal Univ, Sch Math Sci, Nanjing, Jiangsu, Peoples R China
[2] Beifang Univ Nationalities, Sch Math & Informat, Yinchuan, Peoples R China
[3] Ferdowsi Univ Mashhad, Dept Math Sci, Mashhad, Iran
[4] Guilin Univ Elect Technol, Sch Math & Comp Sci, Guilin, Peoples R China
[5] Changsha Univ Sci & Technol, Coll Math & Stat, Changsha, Hunan, Peoples R China
关键词
Three-term conjugate gradient method; sufficient descent condition; quasi-Newton condition; global convergence; affine combination; SUFFICIENT DESCENT PROPERTY; UNCONSTRAINED OPTIMIZATION; GLOBAL CONVERGENCE; LINE SEARCH; ALGORITHM; EQUATIONS; PERFORMANCE; PARAMETER; CHOICES; RISK;
D O I
10.1080/02331934.2017.1295242
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 modified Hestenes-Stiefel conjugate gradient method for unconstrained problems is developed, which can achieves the twin goals of generating sufficient descent direction at each iteration as well as being close to the Newton direction. In our methods, the hybridization parameter can also be obtained based on other kinds of conjugacy conditions. Under mild condition, we establish their global convergence for general objective functions. Numerical experimentation with the new method indicates that it efficiently solves the test problems and therefore is promising.
引用
收藏
页码:759 / 776
页数:18
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