文献类型：期刊文献

英文题名：A new generalized successive-overrelaxation iteration method for solving saddle point problems

作者：Siting, Wu[1]; Liang, Bao[1]; Jingxuan, Huang[1]

机构：[1] School of Science, East China University of Science and Technology, Shanghai, 200237, China

年份：2021

外文期刊名：ACM International Conference Proceeding Series

收录：EI(收录号：20213510827292)

基金：The authors sincerely thank the reviewers and editors for reading the manuscript of this article carefully and giving helpful suggestions for revision. And the first author is very grateful to Associate Professor Bao Liang for his careful guidance.

语种：英文

外文关键词：Matrix algebra - Numerical methods

摘要：Saddle point problems arise in many areas of scientific computing and engineering applications. Several methods are for solving saddle point problems which has appeared in many different applications of scientific computing. This paper proposed a new generalized successive overrelaxation acceleration of positive definite and skew-symmetric splitting iteration method (PSS-GSOR) for solving the large sparse saddle point problem. The new method splits the coefficient matrix by a positive definite matrix and a skew-symmetric matrix, and constructs a new generalized successive overrelaxation iterative method. Theoretical analysis shows that the new method is convergence. And numerical experiments are given to show that the new method is efficient and more competitive than SOR-Like iteration method and GSOR iteration method. In addition, numerical experiment analyzes the sensitivity of the parameters and finds the approximate optimal parameters. ? 2021 ACM.