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Global Convergence of a Nonlinear Conjugate Gradient Method

机译:非线性共轭梯度法的全局收敛性

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摘要

A modified PRP nonlinear conjugate gradient method to solve unconstrained optimization problems is proposed. The important property of the proposed method is that the sufficient descent property is guaranteed independent of any line search. By the use of the Wolfe line search, the global convergence of the proposed method is established for nonconvex minimization. Numerical results show that the proposed method is effective and promising by comparing with the VPRP, CG-DESCENT, and DL~+ methods.
机译:提出了一种改进的PRP非线性共轭梯度法来解决无约束优化问题。所提出的方法的重要特性是,保证了足够的下降特性,而与任何线搜索无关。通过使用Wolfe线搜索,为非凸最小化建立了所提出方法的全局收敛性。数值结果表明,与VPRP,CG-DESCENT和DL〜+方法相比,该方法是有效的和有希望的。

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  • 来源
    《Mathematical Problems in Engineering》 |2011年第3期|p.1-22|共22页
  • 作者单位

    School of Mathematics and Statistics, Chongqing Three Gorges University, Chongqing 404000, China;

    School of Mathematics and Statistics, Chongqing Three Gorges University, Chongqing 404000, China;

    School of Mathematics and Statistics, Chongqing Three Gorges University, Chongqing 404000, China;

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