期刊
OPTIMIZATION
卷 71, 期 6, 页码 1483-1508出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02331934.2020.1812607
关键词
Maximal monotone operator; Legendre function; reflexive banach space; strong convergence; Bregman inverse strongly monotone
资金
- Science and Technology Fund of Thai Nguyen University of Sciences
- RMUTT Research Grant for New Scholar [NSF62D0602]
This paper studies the generalized monotone quasi-inclusion problem and proposes a forward-backward splitting method to solve the problem. By applying the Bregman distance function, the strong convergence of the algorithm is proven and applied to the variational inequality problem. Numerical examples demonstrate the performance of the algorithm.
In this paper, we study the so-calledgeneralized monotone quasi-inclusion problemwhich is a generalization and extension of well-known monotone quasi-inclusion problem. We propose a forward-backward splitting method for solving this problem in the framework of reflexive Banach spaces. Based on Bregman distance function, we prove a strong convergence result of the proposed algorithm to a common zero of the problem. As an application, we apply the main result to the variational inequality problem. Finally, we provide some numerical examples to demonstrate our algorithm performance. The results presented in this paper improve and extend many known results in the literature.
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