A convergent hybrid three-term conjugate gradient method with sufficient descent property for unconstrained optimization

Q3 Mathematics
T. Diphofu, P. Kaelo, A. Tufa
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引用次数: 1

Abstract

Abstract Conjugate gradient methods are very popular for solving large scale unconstrained optimization problems because of their simplicity to implement and low memory requirements. In this paper, we present a hybrid three-term conjugate gradient method with a direction that always satisfies the sufficient descent condition. We establish global convergence of the new method under the weak Wolfe line search conditions. We also report some numerical results of the proposed method compared to relevant methods in the literature.
无约束优化问题的一种具有充分下降性的收敛混合三项共轭梯度法
摘要共轭梯度法具有实现简单、内存要求低等优点,是求解大规模无约束优化问题的常用方法。本文给出了一种方向总是满足充分下降条件的混合三项共轭梯度法。在弱Wolfe线搜索条件下,建立了新方法的全局收敛性。我们还报道了与文献中相关方法比较的一些数值结果。
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
Topological Algebra and its Applications
Topological Algebra and its Applications Mathematics-Algebra and Number Theory
CiteScore
1.20
自引率
0.00%
发文量
12
审稿时长
24 weeks
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