On Block Preconditioners for PDE-Constrained Optimization Problems

On Block Preconditioners for PDE-Constrained Optimization Problems

Year:    2014

Journal of Computational Mathematics, Vol. 32 (2014), Iss. 3 : pp. 272–283

Abstract

Recently, Bai proposed a block-counter-diagonal and a block-counter-triangular preconditioning matrices to precondition the GMRES method for solving the structured system of linear equations arising from the Galerkin finite-element discretizations of the distributed control problems in (Computing 91 (2011) 379-395). He analyzed the spectral properties and derived explicit expressions of the eigenvalues and eigenvectors of the preconditioned matrices. By applying the special structures and properties of the eigenvector matrices of the preconditioned matrices, we derive upper bounds for the 2-norm condition numbers of the eigenvector matrices and give asymptotic convergence factors of the preconditioned GMRES methods with the block-counter-diagonal and the block-counter-triangular preconditioners. Experimental results show that the convergence analyses match well with the numerical results.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.1401-CR4

Journal of Computational Mathematics, Vol. 32 (2014), Iss. 3 : pp. 272–283

Published online:    2014-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    12

Keywords:    PDE-constrained optimization GMRES method Preconditioner Condition number Asymptotic convergence factor.