New Self-Adaptive Algorithms and Inertial Self-Adaptive Algorithms for the Split Variational Inclusion Problems in Hilbert Space

In the field of convex optimization, numerous problems can be modeled as the split variational inclusion problem. In this paper, we want to give self-adaptive algorithms and inertial self-adaptive algorithms to study the split variational inclusion problems. Next, we propose related convergence theo...

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Vydané v:Numerical functional analysis and optimization Ročník 43; číslo 9; s. 1050 - 1068
Hlavní autori: Chuang, Chih-Sheng, Hong, Chung-Chien
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Abingdon Taylor & Francis 04.07.2022
Taylor & Francis Ltd
Predmet:
Adaptive algorithms
Computational geometry
Convexity
Hilbert space
inertial algorithm
inertial self-adaptive algorithm
Optimization
Self-adaptive algorithm
split feasibility problem
split variational inclusion problem
ISSN:0163-0563, 1532-2467
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Shrnutí:In the field of convex optimization, numerous problems can be modeled as the split variational inclusion problem. In this paper, we want to give self-adaptive algorithms and inertial self-adaptive algorithms to study the split variational inclusion problems. Next, we propose related convergence theorems under suitable conditions.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0163-0563
1532-2467
DOI:10.1080/01630563.2022.2084753