A modified PRP conjugate gradient method for unconstrained optimization and nonlinear equations

被引:0
|
作者
Cui, Haijuan [1 ]
机构
[1] Ludong Univ, Sch Math & Stat Sci, Yantai 264025, Peoples R China
关键词
Conjugate gradient method; Global convergence; Unconstrained optimization; Sufficient descent property; Nonlinear equations; CONVERGENCE; ALGORITHM;
D O I
10.1016/j.apnum.2024.07.014
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A modified Polak Ribiere Polyak(PRP) conjugate gradient(CG) method is proposed for solving unconstrained optimization problems. The search direction generated by this method satisfies sufficient descent condition at each iteration and this method inherits one remarkable property of the standard PRP method. Under the standard Armijo line search, the global convergence and the linearly convergent rate of the presented method is established. Some numerical results are given to show the effectiveness of the proposed method by comparing with some existing CG methods.
引用
收藏
页码:296 / 307
页数:12
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