Skip to main content
Log in

A superlinearly convergent projection method for constrained systems of nonlinear equations

  • Published:
Journal of Global Optimization Aims and scope Submit manuscript

Abstract

In this paper, a new projection method for solving a system of nonlinear equations with convex constraints is presented. Compared with the existing projection method for solving the problem, the projection region in this new algorithm is modified which makes an optimal stepsize available at each iteration and hence guarantees that the next iterate is more closer to the solution set. Under mild conditions, we show that the method is globally convergent, and if an error bound assumption holds in addition, it is shown to be superlinearly convergent. Preliminary numerical experiments also show that this method is more efficient and promising than the existing projection method.

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.

Institutional subscriptions

Similar content being viewed by others

References

  1. Calamai P.H., Moré J.J.: Projected gradient methods for linearly constrained problems. Math. Program. 39(1), 93–116 (1987)

    Article  Google Scholar 

  2. Dirkse S.P., Ferris M.C.: MCPLIB: a collection of nonlinear mixed complementarity problems. Optim. Methods Software 5, 319–345 (1995)

    Article  Google Scholar 

  3. El-Hawary M.E.: Optimal Power Flow: Solution Techniques, Requirement and Challenges. IEEE Service Center, Piscataway, NJ (1996)

    Google Scholar 

  4. Kanzow C., Yamashita N., Fukushima M.: Levenberg-Marquardt methods for constrained nonlinear equations with strong local convergence properties. J. Comput. Appl. Math. 172, 375–397 (2004)

    Article  Google Scholar 

  5. Maranas C.D., Floudas C.A.: Finding all solutions of nonlinearly constrained systems of equations. J. Glob. Optim. 7(2), 143–182 (1995)

    Article  Google Scholar 

  6. Meintjes K., Morgan A.P.: A methodology for solving chemical equilibrium systems. Appl. Math. Comput. 22, 333–361 (1987)

    Article  Google Scholar 

  7. Solodov M.V., Svaiter B.F.: A new projection method for variational inequality problems. SIAM J. Control Optim. 37(3), 765–776 (1999)

    Article  Google Scholar 

  8. Solodov M.V., Svaiter B.F.: A truly globally convergent Newton-type method for the monotone nonlinear complementarity problem. SIAM J. Optim. 10, 605–625 (2000)

    Article  Google Scholar 

  9. Tong X.J., Qi L.: On the convergence of a trust-region method for solving constrained nonlinear equations with degenerate solution. J. Optim. Theory Appl. 123, 187–211 (2004)

    Article  Google Scholar 

  10. Wang Y.J., Xiu N.H., Zhang J.Z.: Unified framework of extragradient-type methods for pseudomonotone variational inequalities. J. Optim. Theory Appl. 111, 641–656 (2001)

    Article  Google Scholar 

  11. Wang C.W., Wang Y.J., Xu C.L.: A projection method for a system of nonlinear equtions with convex constraints. Math. Methods Oper. Res. 66, 33–46 (2007)

    Article  Google Scholar 

  12. Wood A.J., Wollenberg B.F.: Power Generations, Operations, and Control. Wiley, New York (1996)

    Google Scholar 

  13. Xiu N.H., Zhang J.Z.: Some recent advances in projection-type methods for variational inequalities. J. Comput. Appl. Math. 152, 559–585 (2003)

    Article  Google Scholar 

  14. Xiu N.H., Wang C.Y., Zhang J.Z.: Convergence properties of projection and contraction methods for variational inequality problems. Appl. Math. Optim. 43, 147–168 (2001)

    Article  Google Scholar 

  15. Yamashita N., Fukushima M.: On the rate of convergence of the Levenberg-Marquardt method. Computing (Suppl.) 15, 237–249 (2001)

    Google Scholar 

  16. Zarantonello E.H.: Projections on convex sets in Hilbert space and spectral theory, contributions to nonlinear functional analysis. In: Zarantonello, E.H. (eds) Contributions to Nonlinear Functional Analysis, Academic Press, New York, NY (1971)

    Google Scholar 

  17. Zhou G.L., Toh K.C.: Superlinear convergence of a Newton-type algorithm for monotone equations. J. Optim. Theory Appl. 125, 205–221 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yiju Wang.

Additional information

This work was done when Yiju Wang visited Chongqing Normal University.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, C., Wang, Y. A superlinearly convergent projection method for constrained systems of nonlinear equations. J Glob Optim 44, 283–296 (2009). https://doi.org/10.1007/s10898-008-9324-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10898-008-9324-8

Keywords

Mathematics Subject Classifications (2000)

Navigation