针对水平线性互补问题的基于模数的通用双松弛两扫矩阵分割迭代法

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-06-25 DOI:10.1007/s11075-024-01860-6

Dan Wang, Jicheng Li

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引用次数: 0

摘要

针对水平线性互补问题（HLCP）的求解，我们提出了一种基于矩阵分裂迭代的一般双松弛两扫模迭代法和一种基于矩阵分裂迭代的双松弛两扫模迭代法。当系统矩阵为（H_+\）矩阵时，我们分析了这些方法的收敛理论。本文中的数值例子说明，这些方法比基于模的矩阵分裂迭代法和一般基于模的矩阵分裂迭代法更有效。

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General double-relaxation two-sweep modulus-based matrix splitting iteration methods for horizontal linear complementarity problem

For solving horizontal linear complementarity problem (HLCP), we propose a general double-relaxation two-sweep modulus-based matrix splitting iteration method and a double-relaxation two-sweep modulus-based matrix splitting iteration method which contain a series of methods, by using different splittings. When the system matrices are \(H_+\)-matrices, we analyze convergence theory of these methods. Numerical examples in this paper illustrate that these methods are more efficient than modulus-based matrix splitting iteration method and general modulus-based matrix splitting iteration method.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.