A self adaptive method for solving a class of bilevel variational inequalities with split variational inequality and composed fixed point problem constraints in Hilbert spaces

IF 1.1 Q2 MATHEMATICS, APPLIED
F. Akutsah, A. A. Mebawondu, H. Abass, O. K. Narain
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引用次数: 1

Abstract

In this work, we propose a new inertial method for solving strongly monotone variational inequality problems over the solution set of a split variational inequality and composed fixed point problem in real Hilbert spaces. Our method uses stepsizes that are generated at each iteration by some simple computations, which allows it to be easily implemented without the prior knowledge of the operator norm as well as the Lipschitz constant of the operator. In addition, we prove that the proposed method converges strongly to a minimum-norm solution of the problem without using the conventional two cases approach. Furthermore, we present some numerical experiments to show the efficiency and applicability of our method in comparison with other methods in the literature. The results obtained in this paper extend, generalize and improve results in this direction.
希尔伯特空间中一类带分裂变分不等式和复合不动点问题约束的双层变分不等式的自适应求解方法
本文提出了一种新的惯性方法,用于求解实数Hilbert空间中分裂变分不等式解集上的强单调变分不等式问题和复合不动点问题。我们的方法使用在每次迭代中通过一些简单的计算生成的步长,这使得它可以很容易地实现,而不需要事先知道算子范数以及算子的Lipschitz常数。此外,我们还证明了该方法不使用传统的两种情况方法,而是强收敛于问题的最小范数解。此外,我们还通过一些数值实验来证明我们的方法与文献中其他方法的有效性和适用性。本文的结果是对这一方向的推广、推广和改进。
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来源期刊
CiteScore
3.10
自引率
0.00%
发文量
62
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.
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