A new generalized shift-splitting method for nonsymmetric saddle point problems. (August 2022)

• Record Type: Journal Article
• Authors: Wei, Tao; Zhang, Li-Tao
• Is Part Of: Advances in mechanical engineering. Volume 14:Number 8(2022)
• Publication Date: 2022-08
• Subjects: Shift-splitting iteration -- nonsymmetric saddle point problems -- convergence -- Krylov subspace methods -- eigenvalue; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/16878132221119451
• Languages: English
• ISSNs: 1687-8132

Abstract

Recently, Huang and Huang [ Journal of Computational and Applied Mathematics, 328 (2018) 381–399] proposed a modified generalized shift-splitting preconditioned (denoted by MGSSP) method for solving large sparse saddle point problems, and gave the corresponding theoretical analysis and numerical experiments. In this paper, based on the modified generalized shift-splitting preconditioned (MGSSP) method, we generalize the MGSSP algorithms and further present the new generalized shift-splitting preconditioned (NGSSP) method for nonsymmetric saddle point problems. Moreover, by similar theoretical analysis, we analyze the convergence conditions of the corresponding matrix splitting iteration methods of the NGSSP preconditioned saddle point matrices. In final, one example is provided to confirm the effectiveness. MSC : 65F10, 65F15, 65F50