{"article_processing_charge":"No","intvolume":" 38","title":"Convergence analysis of projection method for variational inequalities","citation":{"ista":"Shehu Y, Iyiola OS, Li X-H, Dong Q-L. 2019. Convergence analysis of projection method for variational inequalities. Computational and Applied Mathematics. 38(4), 161.","mla":"Shehu, Yekini, et al. “Convergence Analysis of Projection Method for Variational Inequalities.” Computational and Applied Mathematics, vol. 38, no. 4, 161, Springer Nature, 2019, doi:10.1007/s40314-019-0955-9.","short":"Y. Shehu, O.S. Iyiola, X.-H. Li, Q.-L. Dong, Computational and Applied Mathematics 38 (2019).","apa":"Shehu, Y., Iyiola, O. S., Li, X.-H., & Dong, Q.-L. (2019). Convergence analysis of projection method for variational inequalities. Computational and Applied Mathematics. Springer Nature. https://doi.org/10.1007/s40314-019-0955-9","chicago":"Shehu, Yekini, Olaniyi S. Iyiola, Xiao-Huan Li, and Qiao-Li Dong. “Convergence Analysis of Projection Method for Variational Inequalities.” Computational and Applied Mathematics. Springer Nature, 2019. https://doi.org/10.1007/s40314-019-0955-9.","ama":"Shehu Y, Iyiola OS, Li X-H, Dong Q-L. Convergence analysis of projection method for variational inequalities. Computational and Applied Mathematics. 2019;38(4). doi:10.1007/s40314-019-0955-9","ieee":"Y. Shehu, O. S. Iyiola, X.-H. Li, and Q.-L. Dong, “Convergence analysis of projection method for variational inequalities,” Computational and Applied Mathematics, vol. 38, no. 4. Springer Nature, 2019."},"ddc":["510","515","518"],"publication_identifier":{"issn":["2238-3603"],"eissn":["1807-0302"]},"has_accepted_license":"1","article_number":"161","quality_controlled":"1","date_published":"2019-12-01T00:00:00Z","volume":38,"scopus_import":"1","isi":1,"abstract":[{"text":"The main contributions of this paper are the proposition and the convergence analysis of a class of inertial projection-type algorithm for solving variational inequality problems in real Hilbert spaces where the underline operator is monotone and uniformly continuous. We carry out a unified analysis of the proposed method under very mild assumptions. In particular, weak convergence of the generated sequence is established and nonasymptotic O(1 / n) rate of convergence is established, where n denotes the iteration counter. We also present some experimental results to illustrate the profits gained by introducing the inertial extrapolation steps.","lang":"eng"}],"oa":1,"year":"2019","language":[{"iso":"eng"}],"day":"01","author":[{"last_name":"Shehu","orcid":"0000-0001-9224-7139","first_name":"Yekini","id":"3FC7CB58-F248-11E8-B48F-1D18A9856A87","full_name":"Shehu, Yekini"},{"first_name":"Olaniyi S.","last_name":"Iyiola","full_name":"Iyiola, Olaniyi S."},{"first_name":"Xiao-Huan","last_name":"Li","full_name":"Li, Xiao-Huan"},{"full_name":"Dong, Qiao-Li","last_name":"Dong","first_name":"Qiao-Li"}],"main_file_link":[{"url":"https://doi.org/10.1007/s40314-019-0955-9","open_access":"1"}],"ec_funded":1,"oa_version":"Published Version","doi":"10.1007/s40314-019-0955-9","department":[{"_id":"VlKo"}],"project":[{"call_identifier":"FP7","grant_number":"616160","name":"Discrete Optimization in Computer Vision: Theory and Practice","_id":"25FBA906-B435-11E9-9278-68D0E5697425"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_updated":"2023-08-30T07:20:32Z","type":"journal_article","status":"public","article_type":"original","_id":"7000","month":"12","date_created":"2019-11-12T12:41:44Z","publication_status":"published","publisher":"Springer Nature","external_id":{"arxiv":["2101.09081"],"isi":["000488973100005"]},"publication":"Computational and Applied Mathematics","issue":"4"}