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

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Haijuan Cui
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引用次数: 0

Abstract

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.

用于无约束优化和非线性方程的改进型 PRP 共轭梯度法
本文提出了一种改进的 Polak Ribiere Polyak(PRP)共轭梯度(CG)方法,用于解决无约束优化问题。该方法产生的搜索方向在每次迭代时都满足充分下降条件,并且该方法继承了标准 PRP 方法的一个显著特性。在标准 Armijo 线搜索下,建立了该方法的全局收敛性和线性收敛率。通过与一些现有 CG 方法的比较,给出了一些数值结果,以显示所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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