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首页> 外文期刊>Journal of applied mathematics >A Scaled Conjugate Gradient Method for Solving Monotone Nonlinear Equations with Convex Constraints
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A Scaled Conjugate Gradient Method for Solving Monotone Nonlinear Equations with Convex Constraints

机译:求解具有凸约束的单调非线性方程组的比例共轭梯度法

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摘要

Based on the Scaled conjugate gradient (SCALCG) method presented by Andrei (2007) and the projection method presented by Solodov and Svaiter, we propose a SCALCG method for solving monotone nonlinear equations with convex constraints. SCALCG method can be regarded as a combination of conjugate gradient method and Newton-type method for solving unconstrained optimization problems. So, it has the advantages of the both methods. It is suitable for solving large-scale problems. So, it can be applied to solving large-scale monotone nonlinear equations with convex constraints. Under reasonable conditions, we prove its global convergence.We also do some numerical experiments show that the proposed method is efficient and promising.
机译:基于Andrei(2007)提出的比例共轭梯度法(SCALCG)和Solodov和Svaiter提出的投影法,我们提出了一种求解具有凸约束的单调非线性方程的SCALCG方法。 SCALCG方法可以看作是共轭梯度法和牛顿型方法的组合,可以解决无约束优化问题。因此,它具有两种方法的优点。它适用于解决大规模问题。因此,它可以应用于求解具有凸约束的大型单调非线性方程。在合理的条件下,证明了它的全局收敛性。我们还进行了一些数值实验,证明了该方法的有效性和前景。

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