A three-terms Polak-Ribiere-Polyak conjugate gradient algorithm for large-scale nonlinear equations

被引:100
作者
Yuan, Gonglin [1 ]
Zhang, Maojun [2 ,3 ]
机构
[1] Guangxi Univ, Coll Math & Informat Sci, Nanning 530004, Guangxi, Peoples R China
[2] Guilin Univ Elect Technol, Sch Math & Computat Sci, Guangxi Coll, Guangxi 541004, Guilin, Peoples R China
[3] Guilin Univ Elect Technol, Univ Key Lab Data Anal & Computat, Guangxi 541004, Guilin, Peoples R China
关键词
Nonlinear equations; Large-scale; Conjugate gradient; Global convergence; TRUST-REGION METHOD; SUFFICIENT DESCENT PROPERTY; PROJECTION METHOD; BFGS METHOD; SYSTEMS; CONVERGENCE; SPARSE; POINT;
D O I
10.1016/j.cam.2015.03.014
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, a conjugate gradient algorithm for systems of large-scale nonlinear equations is designed by the following steps: (i) A three-terms conjugate gradient direction d(k) is presented where the direction possesses the sufficient descent property and the trust region property independent of line search technique; (ii) A backtracking line search technique along the direction is proposed to get the step length alpha(k) and construct a point; (iii) If the point satisfies the given condition then it is the next point, otherwise the projection-proximal technique is used and get the next point. Both the direction and the line search technique are the derivative-free approaches, then the large-scale nonlinear equations are successfully solved (100,000 variables). The global convergence of the given algorithm is established under suitable conditions. Numerical results show that the proposed method is efficient for large-scale problems. (C) 2015 Published by Elsevier B.V.
引用
收藏
页码:186 / 195
页数:10
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