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The numerical reckoning of modified proximal point methods for minimization problems in non-positive curvature metric spaces

Authors
Thounthong, PhatiphatPakkaranang, NuttapolCho, Yeol JeKumam, WiyadaKumam, Poom
Issue Date
Feb-2020
Publisher
Taylor & Francis
Keywords
CAT(0) spaces; proximal point algorithm; iterative method; nonexapnsive mappings; convex minimization problem
Citation
International Journal of Computer Mathematics, v.97, no.1-2, pp 245 - 262
Pages
18
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Computer Mathematics
Volume
97
Number
1-2
Start Page
245
End Page
262
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/72044
DOI
10.1080/00207160.2018.1551527
ISSN
0020-7160
1029-0265
Abstract
In this paper, we introduce a new modified proximal point algorithm for nonexpansive mappings in non-positive curvature metric spaces and also we prove the sequence generated by the proposed algorithms converges to a common solution between minimization problem and fixed point problem. Moreover, we give some numerical examples to illustrate our main results, that is, our algorithm is more efficient than the algorithm of Cholamjiak et al. and others.
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