Olawale K. Oyewole , Seithuti P. Moshokoa , Sani Salisu , Yekini Shehu
{"title":"随机变分不等式问题的惯性外推Tseng算法分析","authors":"Olawale K. Oyewole , Seithuti P. Moshokoa , Sani Salisu , Yekini Shehu","doi":"10.1016/j.apnum.2025.06.008","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, we design an inertial version of the Tseng extragradient algorithm (also called the Forward-Backward-Forward Algorithm) with self-adaptive step sizes to solve the stochastic variational inequality problem. We prove that the sequence of iterates generated by our proposed algorithm converges to a solution of the stochastic variational inequality problem under mild conditions. Furthermore, we obtain some convergence rates and numerical simulations of our proposed algorithm with comparisons with related algorithms to show the superiority of our algorithm.</div></div>","PeriodicalId":8199,"journal":{"name":"Applied Numerical Mathematics","volume":"217 ","pages":"Pages 199-215"},"PeriodicalIF":2.2000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Tseng algorithm with inertial extrapolation step for stochastic variational inequality problem\",\"authors\":\"Olawale K. Oyewole , Seithuti P. Moshokoa , Sani Salisu , Yekini Shehu\",\"doi\":\"10.1016/j.apnum.2025.06.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this paper, we design an inertial version of the Tseng extragradient algorithm (also called the Forward-Backward-Forward Algorithm) with self-adaptive step sizes to solve the stochastic variational inequality problem. We prove that the sequence of iterates generated by our proposed algorithm converges to a solution of the stochastic variational inequality problem under mild conditions. Furthermore, we obtain some convergence rates and numerical simulations of our proposed algorithm with comparisons with related algorithms to show the superiority of our algorithm.</div></div>\",\"PeriodicalId\":8199,\"journal\":{\"name\":\"Applied Numerical Mathematics\",\"volume\":\"217 \",\"pages\":\"Pages 199-215\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Numerical Mathematics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168927425001254\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Numerical Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168927425001254","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Analysis of Tseng algorithm with inertial extrapolation step for stochastic variational inequality problem
In this paper, we design an inertial version of the Tseng extragradient algorithm (also called the Forward-Backward-Forward Algorithm) with self-adaptive step sizes to solve the stochastic variational inequality problem. We prove that the sequence of iterates generated by our proposed algorithm converges to a solution of the stochastic variational inequality problem under mild conditions. Furthermore, we obtain some convergence rates and numerical simulations of our proposed algorithm with comparisons with related algorithms to show the superiority of our algorithm.
期刊介绍:
The purpose of the journal is to provide a forum for the publication of high quality research and tutorial papers in computational mathematics. In addition to the traditional issues and problems in numerical analysis, the journal also publishes papers describing relevant applications in such fields as physics, fluid dynamics, engineering and other branches of applied science with a computational mathematics component. The journal strives to be flexible in the type of papers it publishes and their format. Equally desirable are:
(i) Full papers, which should be complete and relatively self-contained original contributions with an introduction that can be understood by the broad computational mathematics community. Both rigorous and heuristic styles are acceptable. Of particular interest are papers about new areas of research, in which other than strictly mathematical arguments may be important in establishing a basis for further developments.
(ii) Tutorial review papers, covering some of the important issues in Numerical Mathematics, Scientific Computing and their Applications. The journal will occasionally publish contributions which are larger than the usual format for regular papers.
(iii) Short notes, which present specific new results and techniques in a brief communication.