Another improved Wei-Yao-Liu nonlinear conjugate gradient method with sufficient descent property

被引:58
作者
Dai, Zhifeng [1 ,2 ]
Wen, Fenghua [2 ]
机构
[1] Changsha Univ Sci & Technol, Coll Math & Computat Sci, Changsha 410114, Hunan, Peoples R China
[2] Changsha Univ Sci & Technol, Sch Econometr & Management, Changsha 410114, Hunan, Peoples R China
基金
湖南省自然科学基金;
关键词
Unconstrained optimization; Conjugate gradient method; Sufficient descent property; Global convergence; LINE SEARCH; UNCONSTRAINED OPTIMIZATION; CONVERGENCE PROPERTIES; GLOBAL CONVERGENCE; ALGORITHMS;
D O I
10.1016/j.amc.2011.12.091
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Recently, Zhang [13] take a little modification to the Wei-Yao-Liu nonlinear conjugate gradient method proposed by Wei et al. [10] such that the modified method (called NPRP method in Zhang [13]) satisfies sufficient descent condition with greater parameter sigma is an element of (0, 1/2) in the strong Wolfe line search and converges globally for nonconvex minimization with the strong Wolfe line search. In this paper, we take a little modification to the NPRP method such that the modified NPRP method possesses better properties than the NPRP method in Zhang [13]. Firstly, the modified NPRP method possesses the sufficient descent property without any line searches. Secondly, the modified NPRP method converges globally for nonconvex minimization with Wolfe line search or Armijo line search. Moreover, we extend these results to the Hestenes-Stiefel (HS) method and prove that the modified HS method also possesses sufficient descent property and global convergence with the standard Wolfe conditions. Numerical results are reported by utilizing some test problems in the CUTE library. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:7421 / 7430
页数:10
相关论文
共 24 条
[1]   DESCENT PROPERTY AND GLOBAL CONVERGENCE OF THE FLETCHER REEVES METHOD WITH INEXACT LINE SEARCH [J].
ALBAALI, M .
IMA JOURNAL OF NUMERICAL ANALYSIS, 1985, 5 (01) :121-124
[2]   A Dai-Yuan conjugate gradient algorithm with sufficient descent and conjugacy conditions for unconstrained optimization [J].
Andrei, Neculai .
APPLIED MATHEMATICS LETTERS, 2008, 21 (02) :165-171
[3]   CUTE - CONSTRAINED AND UNCONSTRAINED TESTING ENVIRONMENT [J].
BONGARTZ, I ;
CONN, AR ;
GOULD, N ;
TOINT, PL .
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 1995, 21 (01) :123-160
[4]   A nonlinear conjugate gradient method with a strong global convergence property [J].
Dai, YH ;
Yuan, Y .
SIAM JOURNAL ON OPTIMIZATION, 1999, 10 (01) :177-182
[5]  
Dai Zhifeng, 2005, Mathematica Numerica Sinica, V27, P429
[6]   Benchmarking optimization software with performance profiles [J].
Dolan, ED ;
Moré, JJ .
MATHEMATICAL PROGRAMMING, 2002, 91 (02) :201-213
[7]   FUNCTION MINIMIZATION BY CONJUGATE GRADIENTS [J].
FLETCHER, R ;
REEVES, CM .
COMPUTER JOURNAL, 1964, 7 (02) :149-&
[8]   GLOBAL CONVERGENCE PROPERTIES OF CONJUGATE GRADIENT METHODS FOR OPTIMIZATION [J].
Gilbert, Jean Charles ;
Nocedal, Jorge .
SIAM JOURNAL ON OPTIMIZATION, 1992, 2 (01) :21-42
[9]  
Hager W.W., 2006, Pac. J. Optim., V2, P35
[10]   A new conjugate gradient method with guaranteed descent and an efficient line search [J].
Hager, WW ;
Zhang, HC .
SIAM JOURNAL ON OPTIMIZATION, 2005, 16 (01) :170-192