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首页> 外文期刊>Journal of Mathematics and Statistics >A Robust Modification of Hestenes–Stiefel Conjugate Gradient Method with Strong Wolfe Line Search
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A Robust Modification of Hestenes–Stiefel Conjugate Gradient Method with Strong Wolfe Line Search

机译:HESTENES&NDASH的强大修改; STIEVEL共轭梯度法,具有强大的Wolfe线搜索

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Nonlinear Conjugate Gradient (CG) methods are extensively used for solving large-scale unconstrained optimization problems. Numerous of studies constructed scales and modifications have been conducted recently to improve (CG) methods. In this paper, a simple modified by its conjugate gradient method was proposed. In addition to, established global convergence property and sufficient descent condition, under Strong Wolfe line search. Numerical result shows that the proposed formula is competitive when compared to other well-known (CG) parameters.
机译:非线性缀合物梯度(CG)方法广泛用于解决大规模的无约束优化问题。最近进行了许多研究构造的尺度和修改,以改善(CG)方法。本文提出了一种通过其共轭梯度法改性的简单修改。除了在强大的Wolfe线搜索下建立了全球收敛性和足够的下降条件。数值结果表明,与其他众所周知的(CG)参数相比,所提出的公式是竞争力的。

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