Self-adaptive algorithms for solving split feasibility problem with multiple output sets

Journal article

Authors/Editors

POOM KUMAM

Strategic Research Themes

Other (Strategic Research Themes)

Publication Details

Author list: Taddele, Guash Haile; Kumam, Poom; Sunthrayuth, Pongsakorn; Gebrie, Anteneh Getachew;

Publication year: 2023

Volume number: 92

Issue number: 2

Start page: 1335

End page: 1366

Number of pages: 32

ISSN: 10171398

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134314061&doi=10.1007%2fs11075-022-01343-6&partnerID=40&md5=b4eb570624f9e9101888e50562bf219b

Languages: English-Great Britain (EN-GB)

View in Web of Science | View on publisher site | View citing articles in Web of Science

Abstract

In this paper, we study the split feasibility problem with multiple output sets in Hilbert spaces. For solving the aforementioned problem, we propose two new self-adaptive relaxed CQ algorithms which involve computing of projections onto half-spaces instead of computing onto the closed convex sets, and it does not require calculating the operator norm. We establish a weak and a strong convergence theorems for the proposed algorithms. We apply the new results to solve some other problems. Finally, we present some numerical examples to show the efficiency and accuracy of our algorithm compared to some existing results. Our results extend and improve some existing methods in the literature. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

Split feasibility problem with multiple output sets