Factorization of saddle-point matrices in dynamical systems optimization-reusing pivots

被引：0
|
作者：
Kuratko, Jan [1 ,2 ]
机构：
[1] Charles Univ Prague, Fac Math & Phys, Prague, Czech Republic
[2] Czech Acad Sci, Inst Comp Sci, Pod Vodarenskou Vezi 271-2, Prague, Czech Republic
来源：
LINEAR ALGEBRA AND ITS APPLICATIONS | 2019年 / 566卷
关键词：
Saddle-point matrix; Symmetric indefinite factorization; Dynamical systems; Sequential quadratic programming; SYMMETRIC INDEFINITE SYSTEMS; FINITE-ELEMENTS; EQUATIONS; VERIFICATION; ALGORITHMS;
D O I：
10.1016/j.laa.2018.12.026
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper we consider the application of direct methods for solving a sequence of saddle-point systems. Our goal is to design a method that reuses information from one factorization and applies it to the next one. In more detail, when we compute the pivoted LDLT factorization we speed up computation by reusing already computed pivots and permutations. We develop our method in the frame of dynamical systems optimization. Experiments show that the method improves efficiency over Bunch-Parlett and Bunch-Kaufman while delivering the same results. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码：61 / 85
页数：25
相关论文
共 50 条
12345