具有全局收敛性的共轭梯度系数的新修正

M. Rivaie, M. Fauzi, M. Mamat
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引用次数: 1

摘要

共轭梯度法以其简单、全局收敛的特点在求解无约束优化问题中发挥了重要作用。本文给出了具有全局收敛性的共轭梯度系数(βk)的两个新的修正。通过精确线搜索,得到了全局收敛的结果。比较了另外六个已知的CG系数。性能分析的初步结果表明,与其他CG系数相比,该公式具有一定的竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New modifications of conjugate gradient coefficient with global convergence properties
Conjugate gradient (CG) methods have played an important role in solving unconstrained optimization due to its simplicity and global convergence properties. In this paper, two new modifications of conjugate gradient coefficient (βk) with global convergence properties are presented. The global convergence result is established using exact line searches. Comparisons are made between six others well known CG coefficient. Preliminary result by performance profile shows that the proposed formula is competitive when compared to the other CG coefficients.
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