Skip to main content
Log in

Improved Convergence Result for the Discrete Gradient and Secant Methods for Nonsmooth Optimization

  • Published:
Journal of Optimization Theory and Applications Aims and scope Submit manuscript

Abstract

We study a generalization of the nonderivative discrete gradient method of Bagirov et al. for minimizing a locally Lipschitz function f on ℝn. We strengthen the existing convergence result for this method by showing that it either drives the f-values to −∞ or each of its cluster points is Clarke stationary for f, without requiring the compactness of the level sets of f. Our generalization is an approximate bundle method, which also subsumes the secant method of Bagirov et al.

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. Bagirov, A.M., Karazözen, B., Sezer, M.: Discrete gradient method: Derivative-free method for nonsmooth optimization. J. Optim. Theory Appl. 137, 317–334 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  2. Hiriart-Urruty, J.B., Lemaréchal, C.: Convex Analysis and Minimization Algorithms. Springer, Berlin (1993)

    Google Scholar 

  3. Kiwiel, K.C.: Methods of Descent for Nondifferentiable Optimization. Lecture Notes in Mathematics, vol. 1133. Springer, Berlin (1985)

    MATH  Google Scholar 

  4. Bagirov, A.M., Nazari Ganjehlou, A.: A secant method for nonsmooth optimization. Tech. rep., Centre for Informatics and Applied Optimization, University of Ballarat, Victoria, Australia (2009)

  5. Burke, J.V., Lewis, A.S., Overton, M.L.: A robust gradient sampling algorithm for nonsmooth, nonconvex optimization. SIAM J. Optim. 15, 751–779 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  6. Kiwiel, K.C.: Restricted step and Levenberg-Marquardt techniques in proximal bundle methods for nonconvex nondifferentiable optimization. SIAM J. Optim. 6, 227–249 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  7. Audet, C., Béchard, V., Le Digabel, S.: Nonsmooth optimization through mesh adaptive direct search and variable neighborhood search. J. Glob. Optim. 41, 299–318 (2008)

    Article  MATH  Google Scholar 

  8. Audet, C., Dennis, J.E. Jr.: Mesh adaptive direct search algorithms for constrained optimization. SIAM J. Optim. 17, 188–217 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  9. Clarke, F.H.: Optimization and Nonsmooth Analysis. Wiley, New York (1983)

    MATH  Google Scholar 

  10. Bagirov, A.M., Nazari Ganjehlou, A.: A quasisecant method for minimizing nonsmooth functions. Tech. rep., Centre for Informatics and Applied Optimization, University of Ballarat, Victoria, Australia (2009). Available at the URL http://www.optimization-online.org/DB_FILE/2009/03/2251.pdf

  11. Kiwiel, K.C.: Convergence of the gradient sampling algorithm for nonsmooth nonconvex optimization. SIAM J. Optim. 18, 379–388 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  12. Goldstein, A.A.: Optimization of Lipschitz continuous functions. Math. Program. 13, 14–22 (1977)

    Article  MATH  Google Scholar 

  13. Frangioni, A.: Solving semidefinite quadratic problems within nonsmooth optimization algorithms. Comput. Oper. Res. 23, 1099–1118 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  14. Kiwiel, K.C.: A Cholesky dual method for proximal piecewise linear programming. Numer. Math. 68, 325–340 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  15. Bihain, A.: Optimization of upper semidifferentiable functions. J. Optim. Theory Appl. 44, 545–568 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  16. Lemaréchal, C.: An introduction to the theory of nonsmooth optimization. Optimization 17, 827–858 (1986)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. C. Kiwiel.

Additional information

Communicated by F. Giannessi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kiwiel, K.C. Improved Convergence Result for the Discrete Gradient and Secant Methods for Nonsmooth Optimization. J Optim Theory Appl 144, 69–75 (2010). https://doi.org/10.1007/s10957-009-9584-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10957-009-9584-6

Keywords

Navigation