一类分裂伪单调变分不等式问题的改进外聚算法

IF 1.1 Q2 MATHEMATICS, APPLIED

Numerical Algebra Control and Optimization Pub Date : 2021-01-01 DOI:10.3934/NACO.2021011

G. Ogwo, C. Izuchukwu, O. Mewomo

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引用次数: 17

摘要

本文介绍并研究了实数Hilbert空间中一类分裂伪单调变分不等式问题的一种改进的渐近算法。利用我们提出的算法，我们建立了一个强收敛的结果来逼近上述问题的解。本文的强收敛性结果是在不事先知道本文所用伪单调算子的Lipschitz常数的情况下得到的，并且与文献中关于分裂变分不等式问题的其他结果相比，每次迭代的投影次数最少。最后通过数值算例说明了该方法的性能和优点，并与文献中的相关方法进行了比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A modified extragradient algorithm for a certain class of split pseudo-monotone variational inequality problem

In this paper, we introduce and study a modified extragradient algorithm for approximating solutions of a certain class of split pseudo-monotone variational inequality problem in real Hilbert spaces. Using our proposed algorithm, we established a strong convergent result for approximating solutions of the aforementioned problem. Our strong convergent result is obtained without prior knowledge of the Lipschitz constant of the pseudo-monotone operator used in this paper, and with minimized number of projections per iteration compared to other results on split variational inequality problem in the literature. Furthermore, numerical examples are given to show the performance and advantage of our method as well as comparing it with related methods in the literature.

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来源期刊

Numerical Algebra Control and Optimization MATHEMATICS, APPLIED-

CiteScore

3.10

自引率

0.00%

发文量

期刊介绍： Numerical Algebra, Control and Optimization (NACO) aims at publishing original papers on any non-trivial interplay between control and optimization, and numerical techniques for their underlying linear and nonlinear algebraic systems. Topics of interest to NACO include the following: original research in theory, algorithms and applications of optimization; numerical methods for linear and nonlinear algebraic systems arising in modelling, control and optimisation; and original theoretical and applied research and development in the control of systems including all facets of control theory and its applications. In the application areas, special interests are on artificial intelligence and data sciences. The journal also welcomes expository submissions on subjects of current relevance to readers of the journal. The publication of papers in NACO is free of charge.