A Fast Linearised Augmented Lagrangian Method for a Mean Curvature Based Model
A Fast Linearised Augmented Lagrangian Method for a Mean Curvature Based Model
复制标题
基于平均曲率模型的快速线性增广拉格朗日方法
DOI：
10.4208/eajam.010817.160218
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发表时间：
2018-06
影响因子：
1.2
通讯作者：
Yonggui Zhu
中科院分区：
文献类型：
--
作者：
Jun Zhang;Chengzhi Deng;Yuying Shi;Shengqian Wang;Yonggui Zhu
提出了一种求解平均曲率模型的简单有效的算法。它使用线性化技术，并允许找到所有涉及的子问题的封闭形式的解决方案。实验结果表明，该方法是更有效的CPU时间比增广拉格朗日方法考虑较早。数值算例证明了该方法的收敛性。AMS科目分类：65M55、68U10、94A08
A simple and efficient algorithm for solving a mean curvature based model is proposed. It uses linearisation technique and allows to find closed form solutions of all the subproblems involved. The experimental results show that the method is more efficient in terms of CPU time than the augmented Lagrangian methods considered earlier. Numerical examples demonstrate the convergence of the method. AMS subject classifications: 65M55, 68U10, 94A08