---
_id: '8196'
abstract:
- lang: eng
text: This paper aims to obtain a strong convergence result for a Douglas–Rachford
splitting method with inertial extrapolation step for finding a zero of the sum
of two set-valued maximal monotone operators without any further assumption of
uniform monotonicity on any of the involved maximal monotone operators. Furthermore,
our proposed method is easy to implement and the inertial factor in our proposed
method is a natural choice. Our method of proof is of independent interest. Finally,
some numerical implementations are given to confirm the theoretical analysis.
acknowledgement: Open access funding provided by Institute of Science and Technology
(IST Austria). The project of Yekini Shehu has received funding from the European
Research Council (ERC) under the European Union’s Seventh Framework Program (FP7—2007–2013)
(Grant Agreement No. 616160). The authors are grateful to the anonymous referees
and the handling Editor for their comments and suggestions which have improved the
earlier version of the manuscript greatly.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Yekini
full_name: Shehu, Yekini
id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87
last_name: Shehu
orcid: 0000-0001-9224-7139
- first_name: Qiao-Li
full_name: Dong, Qiao-Li
last_name: Dong
- first_name: Lu-Lu
full_name: Liu, Lu-Lu
last_name: Liu
- first_name: Jen-Chih
full_name: Yao, Jen-Chih
last_name: Yao
citation:
ama: Shehu Y, Dong Q-L, Liu L-L, Yao J-C. New strong convergence method for the
sum of two maximal monotone operators. Optimization and Engineering. 2021;22:2627-2653.
doi:10.1007/s11081-020-09544-5
apa: Shehu, Y., Dong, Q.-L., Liu, L.-L., & Yao, J.-C. (2021). New strong convergence
method for the sum of two maximal monotone operators. Optimization and Engineering.
Springer Nature. https://doi.org/10.1007/s11081-020-09544-5
chicago: Shehu, Yekini, Qiao-Li Dong, Lu-Lu Liu, and Jen-Chih Yao. “New Strong Convergence
Method for the Sum of Two Maximal Monotone Operators.” Optimization and Engineering.
Springer Nature, 2021. https://doi.org/10.1007/s11081-020-09544-5.
ieee: Y. Shehu, Q.-L. Dong, L.-L. Liu, and J.-C. Yao, “New strong convergence method
for the sum of two maximal monotone operators,” Optimization and Engineering,
vol. 22. Springer Nature, pp. 2627–2653, 2021.
ista: Shehu Y, Dong Q-L, Liu L-L, Yao J-C. 2021. New strong convergence method for
the sum of two maximal monotone operators. Optimization and Engineering. 22, 2627–2653.
mla: Shehu, Yekini, et al. “New Strong Convergence Method for the Sum of Two Maximal
Monotone Operators.” Optimization and Engineering, vol. 22, Springer Nature,
2021, pp. 2627–53, doi:10.1007/s11081-020-09544-5.
short: Y. Shehu, Q.-L. Dong, L.-L. Liu, J.-C. Yao, Optimization and Engineering
22 (2021) 2627–2653.
date_created: 2020-08-03T14:29:57Z
date_published: 2021-02-25T00:00:00Z
date_updated: 2024-03-07T14:39:29Z
day: '25'
ddc:
- '510'
department:
- _id: VlKo
doi: 10.1007/s11081-020-09544-5
ec_funded: 1
external_id:
isi:
- '000559345400001'
file:
- access_level: open_access
content_type: application/pdf
creator: dernst
date_created: 2020-08-03T15:24:39Z
date_updated: 2020-08-03T15:24:39Z
file_id: '8197'
file_name: 2020_OptimizationEngineering_Shehu.pdf
file_size: 2137860
relation: main_file
success: 1
file_date_updated: 2020-08-03T15:24:39Z
has_accepted_license: '1'
intvolume: ' 22'
isi: 1
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 2627-2653
project:
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Optimization and Engineering
publication_identifier:
eissn:
- 1573-2924
issn:
- 1389-4420
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: New strong convergence method for the sum of two maximal monotone operators
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 22
year: '2021'
...