Convergence of a Class of Stationary Iterative Methods for Saddle Point Problems

作     者：Yin Zhang 

作者机构：Institute for Data and Decision AnalyticsThe Chinese University of Hong KongShenzhen 518172China Department of Computational and Applied MathematicsRice UniversityHouston 77005United States of America 

出 版 物：《Journal of the Operations Research Society of China》 (中国运筹学会会刊（英文）)

年 卷 期：2019年第7卷第2期

页      面：195-204页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：This paper is a polished version of the Rice University technical report CAAMTR10-24 which was a work supported in part by the National Natural Science Foundation(No.DMS-0811188) Office of Navy Research(No.N00014-08-1-1101) 

主　　题：Saddle point problem Quadratic program Matrix splitting Stationary iterations Spectral radius Q-linear convergence 

摘      要：A unified convergence theory is derived for a class of stationary iterative methods for solving linear equality constrained quadratic programs or saddle point *** class is constructed from essentially all possible splittings of the submatrix residing in the(1,1)-block of the augmented saddle point matrix that would produce non-expansive *** classic augmented Lagrangian method and alternating direction method of multipliers are two special members of this class.