无约束优化问题的一种新的全局收敛共轭梯度系数法

Mardeen Sh. Taher, S. Shareef
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引用次数: 0

摘要

本文定义了求解非线性无约束优化问题的共轭梯度法的一个新的系数公式。新公式β新k是直线搜索的类型,我们的工作重点是修改佩里的建议。进一步证明了在Wolf-Powell线搜索下,新公式的全局收敛结果是可识别的。结果表明,新的CG系数满足下降的充分条件。最后,用测试函数集合进行了数值实验,结果表明,与β H−S k、β Perry k和β D−Y k等标准公式相比,new β new k更为有效。
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A New Coefficient of Conjugate Gradient Method with Global Convergence for Unconstrained Optimization Problems
In this article, we defined a new coefficient formula of the conjugate gradient method for solving non linear unconstrained optimization problems. The new formula β new k is type of line search and the idea of our work is to focus on modification the Perry’s suggestion. We further show that global convergence result of new formula is recognized under Wolf-Powell line search. It is shown that the new CG coefficient satisfied sufficient descent conditions. In the end, numerical experiments with the collection of test functions show that the new β new k is more effective compared to some other standard formulas such as β H−S k , β Perry k and β D−Y k .
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审稿时长
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