Using constraint preconditioners with regularized saddle-point problems

• Published in: Computational optimization and applications Vol. 36; no. 2-3; pp. 249 - 270
• Main Authors: Dollar, H S, Gould, N I M, Schilders, W H A, Wathen, A J
• Format: Journal Article
• Language: English
• Published: New York Springer Nature B.V 01.04.2007
• Subjects: Eigenvalues; Laboratories; Linear programming; Mathematical models; Optimization; Problem solving; Studies
• ISSN: 0926-6003; 1573-2894
• DOI: 10.1007/s10589-006-9004-x

The problem of finding good preconditioners for the numerical solution of a certain important class of indefinite linear systems is considered. These systems are of a 2 by 2 block (KKT) structure in which the (2,2) block (denoted by -C) is assumed to be nonzero. In Constraint preconditioning for indefinite linear systems, SIAM J. Matrix Anal. Appl. 21 (2000), Keller, Gould and Wathen introduced the idea of using constraint preconditioners that have a specific 2 by 2 block structure for the case of C being zero. We shall give results concerning the spectrum and form of the eigenvectors when a preconditioner of the form considered by Keller, Gould and Wathen is used but the system we wish to solve may have C ?0. In particular, the results presented here indicate clustering of eigenvalues and, hence, faster convergence of Krylov subspace iterative methods when the entries of C are small; such a situations arise naturally in interior point methods for optimization and we present results for such problems which validate our conclusions.[PUBLICATION ABSTRACT]