Skip to main content
Log in

Using constraint preconditioners with regularized saddle-point problems

  • Published:
Computational Optimization and Applications Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Axelsson, O., Barker, V.A.: Finite Element Solution of Boundary Value Problems. Theory and Computation, Classics in Applied Mathematics, vol. 35. SIAM, Philadelphia (2001). Reprint of the 1984 original

    MATH  Google Scholar 

  2. Benzi, M., Golub, G.H., Liesen, J.: Numerical solution of saddle point problems. Acta Numer. 14, 1–137 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  3. Bergamaschi, L., Gondzio, J., Zilli, G.: Preconditioning indefinite systems in interior point methods for optimization. Comput. Optim. Appl. 28, 149–171 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  4. Cafieri, S., D’Apuzzo, M., De Simone, V., di Serafino, D.: On the iterative solution of KKT systems in potential reduction software for large-scale quadratic problems. Technical Report 09/2004, Dept. of Mathematics, Second University of Naples (December 2004). Comput. Optim. Appl. (to appear)

  5. Dollar, H.S.: Constraint-style preconditioners for regularized saddle-point problems. Technical Report 3/2006, Dept. of Mathematics, University of Reading (March 2006). SIAM J. Matrix Anal. Appl. (to appear)

  6. Dollar, H.S.: Iterative linear algebra for constrained optimization. Thesis of Doctor of Philosophy. Oxford University (2005)

  7. Elman, H.C., Silvester, D.J., Wathen, A.J.: Finite Elements and Fast Iterative Solvers: with Applications in Incompressible Fluid Dynamics. Oxford University Press, Oxford (2005)

    MATH  Google Scholar 

  8. Forsgren, A., Gill, P.E., Griffin, J.D.: Iterative solution of augmented systems arising in interior methods. Technical Report NA-05-03, University of California, San Diego (August 2005)

  9. Freund, R.W., Nachtigal, N.M.: A new Krylov-subspace method for symmetric indefinite linear systems. In: Ames, W.F. (ed.) Proceedings of the 14th IMACS World Congress on Computational and Applied Mathematics, pp. 1253–1256. IMACS (1994)

  10. Golub, G.H., Van Loan, C.F.: Matrix Computations, 3rd edn., Johns Hopkins Studies in the Mathematical Sciences. Johns Hopkins University Press, Baltimore (1996)

    MATH  Google Scholar 

  11. Gould, N.I.M.: On the accurate determination of search directions for simple differentiable penalty functions. IMA J. Numer. Anal. 6, 357–372 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  12. Gould, N.I.M., Hribar, M.E., Nocedal, J.: On the solution of equality constrained quadratic programming problems arising in optimization. SIAM J. Sci. Comput. 23, 1376–1395 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  13. Gould, N.I.M., Orban, D., Toint, P.L.: CUTEr and SifDec: a constrained and unconstrained testing environment, revisited. ACM Trans. Math. Software 29, 373–394 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  14. Greenbaum, A.: Iterative Methods for Solving Linear Systems. Frontiers in Applied Mathematics, vol. 17. SIAM, Philadelphia (1997)

    MATH  Google Scholar 

  15. Greenbaum, A., Pták, V., Strakoš, Z.: Any nonincreasing convergence curve is possible for GMRES. SIAM J. Matrix Anal. Appl. 17, 465–469 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  16. Keller, C., Gould, N.I.M., Wathen, A.J.: Constraint preconditioning for indefinite linear systems. SIAM J. Matrix Anal. Appl. 21, 1300–1317 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  17. Lukšan, L., Vlček, J.: Indefinitely preconditioned inexact Newton method for large sparse equality constrained non-linear programming problems. Numer. Linear Algebra Appl. 5, 219–247 (1998)

    Article  MathSciNet  Google Scholar 

  18. Perugia, I., Simoncini, V.: Block-diagonal and indefinite symmetric preconditioners for mixed finite element formulations. Numer. Linear Algebra Appl. 7, 585–616 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  19. Rozložník, M., Simoncini, V.: Krylov subspace methods for saddle point problems with indefinite preconditioning. SIAM J. Matrix Anal. Appl. 24, 368–391 (2002)

    Article  MathSciNet  Google Scholar 

  20. Saad, Y.: Iterative Methods for Sparse Linear Systems, 2nd edn. SIAM, Philadelphia (2003)

    MATH  Google Scholar 

  21. Saad, Y., Schultz, M.H.: GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 7, 856–869 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  22. Tisseur, F., Meerbergen, K.: The quadratic eigenvalue problem. SIAM Rev. 43, 235–286 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  23. Toh, K.-C., Phoon, K.-K., Chan, S.-H.: Block preconditioners for symmetric indefinite linear systems. Int. J. Numer. Methods Eng. 60, 1361–1381 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  24. Wright, S.J.: Primal–Dual Interior-Point Methods. SIAM, Philadelphia (1997)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. S. Dollar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dollar, H.S., Gould, N.I.M., Schilders, W.H.A. et al. Using constraint preconditioners with regularized saddle-point problems. Comput Optim Appl 36, 249–270 (2007). https://doi.org/10.1007/s10589-006-9004-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10589-006-9004-x

Keywords

Navigation