New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings

New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings

© 2019, University of Nis. All rights reserved. In this paper, we introduce two hybrid algorithms for finding a common best proximity point of two best proximally nonexpansive mappings. We establish strong convergence theorems of the proposed algorithms under some control conditions in a real Hilber...

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Main Authors: Jenwit Puangpee, Suthep Suantai
Format: Journal
Published: 2020
Subjects:
Mathematics
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078289053&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/67911
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Institution: Chiang Mai University
id th-cmuir.6653943832-67911
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spelling th-cmuir.6653943832-679112020-04-02T15:11:14Z New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings Jenwit Puangpee Suthep Suantai Mathematics © 2019, University of Nis. All rights reserved. In this paper, we introduce two hybrid algorithms for finding a common best proximity point of two best proximally nonexpansive mappings. We establish strong convergence theorems of the proposed algorithms under some control conditions in a real Hilbert space. Moreover, some numerical examples are given for supporting our main theorems. 2020-04-02T15:11:14Z 2020-04-02T15:11:14Z 2019-01-01 Journal 03545180 2-s2.0-85078289053 10.2298/FIL1908381P https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078289053&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/67911
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Mathematics
spellingShingle Mathematics
Jenwit Puangpee
Suthep Suantai
New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
description © 2019, University of Nis. All rights reserved. In this paper, we introduce two hybrid algorithms for finding a common best proximity point of two best proximally nonexpansive mappings. We establish strong convergence theorems of the proposed algorithms under some control conditions in a real Hilbert space. Moreover, some numerical examples are given for supporting our main theorems.
format Journal
author Jenwit Puangpee
Suthep Suantai
author_facet Jenwit Puangpee
Suthep Suantai
author_sort Jenwit Puangpee
title New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
title_short New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
title_full New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
title_fullStr New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
title_full_unstemmed New hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
title_sort new hybrid algorithms for global minimization of common best proximity points of some generalized nonexpansive mappings
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078289053&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/67911
_version_ 1681426722687287296

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