Open AccessTwo self-adaptive inertial projection algorithms for solving split variational inclusion problems
Author(s) -
Zheng Zhou,
AUTHOR_ID,
Bing Tan,
Songxiao Li
Publication year - 2022
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2022276
Subject(s) - convergence (economics) , hilbert space , algorithm , inertial frame of reference , projection (relational algebra) , mathematics , projection method , dykstra's projection algorithm , computer science , mathematical optimization , mathematical analysis , economic growth , physics , quantum mechanics , economics
This paper is to analyze the approximation solution of a split variational inclusion problem in the framework of Hilbert spaces. For this purpose, inertial hybrid and shrinking projection algorithms are proposed under the effect of a self-adaptive stepsize which does not require information of the norms of the given operators. The strong convergence properties of the proposed algorithms are obtained under mild constraints. Finally, a numerical experiment is given to illustrate the performance of proposed methods and to compare our algorithms with an existing algorithm.