首页> 外文期刊>Journal of industrial and management optimization >NONLINEAR CONJUGATE GRADIENT METHODS WITH SUFFICIENT DESCENT PROPERTIES FOR UNCONSTRAINED OPTIMIZATION
【24h】

NONLINEAR CONJUGATE GRADIENT METHODS WITH SUFFICIENT DESCENT PROPERTIES FOR UNCONSTRAINED OPTIMIZATION

机译:具有充分下降性质的非线性共轭梯度法用于无约束优化

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

It is very important to generate a descent search direction independent of line searches in showing the global convergence of conjugate gradient methods. The method of Hager and Zhang (2005) satisfies the sufficient descent condition. In this paper, we treat two subjects. We first consider a unified formula of parameters which establishes the sufficient descent condition and follows the modification technique of Hager and Zhang. In order to show the global convergence of the conjugate gradient method with the unified formula of parameters, we define some property (say Property A). We prove the global convergence of the method with Property A. Next, we apply the unified formula to a scaled conjugate gradient method and show its global convergence property. Finally numerical results are given.
机译:在显示共轭梯度方法的全局收敛性时,生成与线搜索无关的下降搜索方向非常重要。 Hager和Zhang(2005)的方法满足了充分的下降条件。在本文中,我们处理两个主题。我们首先考虑统一的参数公式,该公式建立了充分的下降条件并遵循Hager和Zhang的修改技术。为了显示具有参数统一公式的共轭梯度法的全局收敛性,我们定义了一些属性(例如,属性A)。我们用性质A证明了该方法的全局收敛性。接下来,我们将统一公式应用于比例共轭梯度法,并显示其全局收敛性。最后给出数值结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号