{"title":"C-FISTA type projection algorithm for quasi-variational inequalities","authors":"Yonghong Yao, Lateef O. Jolaoso, Yekini Shehu","doi":"10.1007/s11075-024-01852-6","DOIUrl":null,"url":null,"abstract":"<p>In this paper, we first propose a version of FISTA, called C-FISTA type gradient projection algorithm, for quasi-variational inequalities in Hilbert spaces and obtain linear convergence rate. Our results extend the results of Nesterov for C-FISTA algorithm for strongly convex optimization problem and other recent results in the literature where linear convergence results of C-FISTA are obtained for strongly convex composite optimization problems. For a comprehensive study, we also introduce a new version of gradient projection algorithm with momentum terms and give linear rate of convergence. We show the adaptability and effectiveness of our proposed algorithms through numerical comparisons with other related gradient projection algorithms that are in the literature for quasi-variational inequalities.</p>","PeriodicalId":54709,"journal":{"name":"Numerical Algorithms","volume":"33 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Numerical Algorithms","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11075-024-01852-6","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we first propose a version of FISTA, called C-FISTA type gradient projection algorithm, for quasi-variational inequalities in Hilbert spaces and obtain linear convergence rate. Our results extend the results of Nesterov for C-FISTA algorithm for strongly convex optimization problem and other recent results in the literature where linear convergence results of C-FISTA are obtained for strongly convex composite optimization problems. For a comprehensive study, we also introduce a new version of gradient projection algorithm with momentum terms and give linear rate of convergence. We show the adaptability and effectiveness of our proposed algorithms through numerical comparisons with other related gradient projection algorithms that are in the literature for quasi-variational inequalities.
期刊介绍：
The journal Numerical Algorithms is devoted to numerical algorithms. It publishes original and review papers on all the aspects of numerical algorithms: new algorithms, theoretical results, implementation, numerical stability, complexity, parallel computing, subroutines, and applications. Papers on computer algebra related to obtaining numerical results will also be considered. It is intended to publish only high quality papers containing material not published elsewhere.
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