{"title":"解决标准非线性伪单调方程和逻辑回归问题的基于两步放松惯性无导数投影算法","authors":"Wenli Liu , Jinbao Jian , Jianghua Yin","doi":"10.1016/j.cam.2024.116327","DOIUrl":null,"url":null,"abstract":"<div><div>This paper explores a two-step inertial derivative-free projection method with a relaxation factor <span><math><mrow><mi>γ</mi><mo>∈</mo><mrow><mo>(</mo><mn>0</mn><mo>,</mo><mn>2</mn><mo>)</mo></mrow></mrow></math></span> for solving nonlinear pseudo-monotone equations. Unlike existing inertial algorithms for the system of nonlinear pseudo-monotone equations, the inertial step of our method involves the current iteration point and the previous two iteration points. In particular, one of the inertial parameters is nonpositive. In the proposed algorithm, the search direction possesses not only the sufficient descent property but also the trust region property, independent of the line search technique. Moreover, we also establish the global convergence and the convergence rate of the algorithm without the Lipschitz continuity of the underlying mapping. Finally, our method provides competitive results on standard nonlinear monotone and pseudo-monotone equations and logistic regression problems compared with two inertial algorithms existing in the literature.</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"457 ","pages":"Article 116327"},"PeriodicalIF":2.1000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A two-step relaxed-inertial derivative-free projection based algorithm for solving standard nonlinear pseudo-monotone equations and logistic regression problems\",\"authors\":\"Wenli Liu , Jinbao Jian , Jianghua Yin\",\"doi\":\"10.1016/j.cam.2024.116327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper explores a two-step inertial derivative-free projection method with a relaxation factor <span><math><mrow><mi>γ</mi><mo>∈</mo><mrow><mo>(</mo><mn>0</mn><mo>,</mo><mn>2</mn><mo>)</mo></mrow></mrow></math></span> for solving nonlinear pseudo-monotone equations. Unlike existing inertial algorithms for the system of nonlinear pseudo-monotone equations, the inertial step of our method involves the current iteration point and the previous two iteration points. In particular, one of the inertial parameters is nonpositive. In the proposed algorithm, the search direction possesses not only the sufficient descent property but also the trust region property, independent of the line search technique. Moreover, we also establish the global convergence and the convergence rate of the algorithm without the Lipschitz continuity of the underlying mapping. Finally, our method provides competitive results on standard nonlinear monotone and pseudo-monotone equations and logistic regression problems compared with two inertial algorithms existing in the literature.</div></div>\",\"PeriodicalId\":50226,\"journal\":{\"name\":\"Journal of Computational and Applied Mathematics\",\"volume\":\"457 \",\"pages\":\"Article 116327\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational and Applied Mathematics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0377042724005752\",\"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":"Journal of Computational and Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377042724005752","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
A two-step relaxed-inertial derivative-free projection based algorithm for solving standard nonlinear pseudo-monotone equations and logistic regression problems
This paper explores a two-step inertial derivative-free projection method with a relaxation factor for solving nonlinear pseudo-monotone equations. Unlike existing inertial algorithms for the system of nonlinear pseudo-monotone equations, the inertial step of our method involves the current iteration point and the previous two iteration points. In particular, one of the inertial parameters is nonpositive. In the proposed algorithm, the search direction possesses not only the sufficient descent property but also the trust region property, independent of the line search technique. Moreover, we also establish the global convergence and the convergence rate of the algorithm without the Lipschitz continuity of the underlying mapping. Finally, our method provides competitive results on standard nonlinear monotone and pseudo-monotone equations and logistic regression problems compared with two inertial algorithms existing in the literature.
期刊介绍:
The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest.
The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.