Skip to main content

A Hybrid Newton-GMRES Method for Solving Nonlinear Equations

  • Conference paper
  • First Online:
Book cover Numerical Analysis and Its Applications (NAA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1988))

Included in the following conference series:

Abstract

A subspace linesearch strategy for the globalization of Newton-GMRES method is proposed. The main feature of our proposal is the simple and inexpensive way we determine descent directions in the low-dimensional subspaces generated by GMRES. Global and local quadratic convergence is established under standard assumptions.

This work was partially supported by Murst Cofin98 ”Metodologie numeriche avanzate per il calcolo scientifico”, CNR “Progetto coordinato sistemi di calcolo di grandi dimensioni e calcolo parallelo▸, Rome, Italy

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bellavia S., Morini B.: A globally convergent Newton-GMRES subspace method for systems of nonlinear equations. Submitted for publication.

    Google Scholar 

  2. Brown P. N., Saad Y.: Hybrid Krylov Methods for nonlinear systems of equations. SIAM J. Sci. Stat. Comput. 11 (1990) 450–481.

    Article  MATH  MathSciNet  Google Scholar 

  3. Brown P. N., Saad Y.: Convergence Theory of Nonlinear Newton-Krylov algorithms. SIAM J. Optim. 4 (1994) 297–330.

    Article  MATH  MathSciNet  Google Scholar 

  4. Dembo R. S., Eisenstat S. C., Steihaug T.: Inexact Newton Methods. SIAM J. Numer. Anal. 19 (1982) 400–408.

    Article  MATH  MathSciNet  Google Scholar 

  5. Dennis J. E., Schnabel R. B.: Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice Hall, Englewood Cliffs, NJ, 1983.

    MATH  Google Scholar 

  6. Eisenstat S. C., Walker H. F.: Globally Convergent Inexact Newton Methods. SIAM J. Optim. 4 (1994) 393–422.

    Article  MATH  MathSciNet  Google Scholar 

  7. Feng D., Pulliam T. H.: Tensor-GMRES method for large systems of nonlinear equations. SIAM J. Optim. 7 (1997) 757–779.

    Article  MATH  MathSciNet  Google Scholar 

  8. Kelley C. T.: Iterative Methods for Linear and Nonlinear Equations. SIAM, Philadelphia, 1995

    Google Scholar 

  9. Pernice M., Walker H. F.: NITSOL: a new iterative solver for nonlinear systems. SIAM J. Sci Comput. 19 (1998) 302–318.

    Article  MATH  MathSciNet  Google Scholar 

  10. Saad Y., SchultzM. H.: GMRES: a generalized minimal residual method for solving nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 6 (1985) 856–869.

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bellavia, S., Macconi, M., Morini, B. (2001). A Hybrid Newton-GMRES Method for Solving Nonlinear Equations. In: Vulkov, L., Yalamov, P., Waśniewski, J. (eds) Numerical Analysis and Its Applications. NAA 2000. Lecture Notes in Computer Science, vol 1988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45262-1_9

Download citation

  • DOI: https://doi.org/10.1007/3-540-45262-1_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41814-6

  • Online ISBN: 978-3-540-45262-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics