Modified PSS-GSOR method for solving saddle point problem

Jinpin Huang; Gengwei Zhao; Rui Bai; Yun Xu

doi:10.1117/12.2639103

17 May 2022 Modified PSS-GSOR method for solving saddle point problem

Jinpin Huang, Gengwei Zhao, Rui Bai, Yun Xu

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 122590S (2022) https://doi.org/10.1117/12.2639103
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

Large-scale saddle-point linear systems appear in computational science and engineering fields such as fluid mechanics, image localization, parameter identification and constraint optimization. For a class of asymmetric saddle point problems, the defects of PSS-GSOR iteration are analyzed, and a modified iteration method is constructed. The main idea is to introduce new parameters to improve the sensitivity of iterative correlation coefficient matrix, and give a reasonable selection method of parameter positive definite matrix. According to the characteristics of the established iterative scheme, the convergence of the given iteration is proved by using the matrix eigenvalue theory, and the range of relevant parameters is obtained. Finally, through numerical experiments, the effectiveness of the modified PSS-GSOR method for solving saddle point problems is verified by comparison.

Citation Download Citation

Jinpin Huang, Gengwei Zhao, Rui Bai, and Yun Xu "Modified PSS-GSOR method for solving saddle point problem", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 122590S (17 May 2022); https://doi.org/10.1117/12.2639103

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