Global convergence of some modified PRP nonlinear conjugate gradient methods

被引：0
作者：
Zhi-feng Dai
Bo-Shi Tian
机构：
[1] Hunan University,College of Mathematics and Econometrics
[2] Changsha University of Science and Technology,College of Mathematics and Computational Science
来源：
Optimization Letters | 2011年 / 5卷
关键词：
Unconstrained optimization; Conjugate gradient method; Line search; Sufficient descent property; Global convergence;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Recently, similar to Hager and Zhang (SIAM J Optim 16:170–192, 2005), Yu (Nonlinear self-scaling conjugate gradient methods for large-scale optimization problems. Thesis of Doctors Degree, Sun Yat-Sen University, 2007) and Yuan (Optim Lett 3:11–21, 2009) proposed modified PRP conjugate gradient methods which generate sufficient descent directions without any line searches. In order to obtain the global convergence of their algorithms, they need the assumption that the stepsize is bounded away from zero. In this paper, we take a little modification to these methods such that the modified methods retain sufficient descent property. Without requirement of the positive lower bound of the stepsize, we prove that the proposed methods are globally convergent. Some numerical results are also reported.
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页码：615 / 630
页数：15
相关论文
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