Skip to main content
Log in

Globally Convergent Cutting Plane Method for Nonconvex Nonsmooth Minimization

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

Abstract

Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms developed so far deal only with nonsmooth convex functions. In this paper, we propose a new algorithm for solving nonsmooth optimization problems that are not assumed to be convex. The algorithm combines the traditional cutting plane method with some features of bundle methods, and the search direction calculation of feasible direction interior point algorithm (Herskovits, J. Optim. Theory Appl. 99(1):121–146, 1998). The algorithm to be presented generates a sequence of interior points to the epigraph of the objective function. The accumulation points of this sequence are solutions to the original problem. We prove the global convergence of the method for locally Lipschitz continuous functions and give some preliminary results from numerical experiments.

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. Cheney, E.W., Goldstein, A.A.: Newton’s method for convex programming and Tchebycheff approximation. Numer. Math. 1, 253–268 (1959)

    Article  MATH  MathSciNet  Google Scholar 

  2. Kelley, J.E.: The cutting plane method for solving convex programs. J. Soc. Ind. Appl. Math. 8, 703–712 (1960)

    Article  MathSciNet  Google Scholar 

  3. Herskovits, J.: Feasible direction interior-point technique for nonlinear optimization. J. Optim. Theory Appl. 99(1), 121–146 (1998)

    Article  MATH  MathSciNet  Google Scholar 

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

    MATH  Google Scholar 

  5. Mäkelä, M.M., Neittaanmäki, P.: Nonsmooth Optimization: Analysis and Algorithms with Applications to Optimal Control. World Scientific, Singapore (1992)

    MATH  Google Scholar 

  6. Schramm, H., Zowe, J.: A version of the bundle idea for minimizing a nonsmooth function: conceptual idea, convergence analysis, numerical results. SIAM J. Optim. 2(1), 121–152 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  7. Herskovits, J., Freire, W., Tanaka Filho, M.: A feasible directions method for nonsmooth convex optimization. Technical Report, Mechanical Engineering Program-COPPE/UFRJ, Rio de Janeiro, julho (2009). Available in web page http://www.optimization-online.org/DB_HTML/2010/01/2517.html (January 11th, 2010)

  8. Passarela, W.: An algorithm of feasible directions to nonsmooth convex optimization (in Portuguese). PhD thesis, COPPE—Federal University of Rio de Janeiro, Mechanical Engineering Program, Rio de Janeiro, Brazil (2005)

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

    MATH  Google Scholar 

  10. Fuduli, A., Gaudioso, M., Giallombardo, G.: A DC piecewise affine model and a bundling technique in nonconvex nonsmooth minimization. Optim. Methods Softw. 19(1), 89–102 (2004)

    Article  MATH  MathSciNet  Google Scholar 

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

    MATH  Google Scholar 

  12. Tits, A.L., Wächter, A., Bakhtiari, S., Urban, T.J., Lawrence, C.T.: A primal-dual interior-point method for nonlinear programming with strong global and local convergence properties. SIAM J. Optim. 14(1), 173–199 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  13. Panier, E.R., Tits, A.L., Herskovits, J.N.: A QP-free, globally convergent, locally superlinearly convergent algorithm for inequality constrained optimization. SIAM J. Control Optim. 26(4), 788–811 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  14. Lukšan, L., Vlček, J.: Test problems for nonsmooth unconstrained and linearly constrained optimization. Technical Report 798, Institute of Computer Science, Academy of Sciences of the Czech Republic, Prague (2000)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Napsu Karmitsa.

Additional information

Communicated by P.M. Pardalos.

The authors would like to thank Prof. Marko M. Mäkelä (University of Turku, Finland) for the valuable comments and Prof. Tapio Westerlund (Abo Akademi University, Finland) for financial support. The work was financially supported by the Research Councils CAPES, CNPq and Faperj (Brazil), COPPE/Federal University of Rio de Janeiro (Brazil), University of Turku (Finland), Magnus Ehrnrooth foundation (Finland), and the Academy of Finland (Project No. 127992).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Karmitsa, N., Tanaka Filho, M. & Herskovits, J. Globally Convergent Cutting Plane Method for Nonconvex Nonsmooth Minimization. J Optim Theory Appl 148, 528–549 (2011). https://doi.org/10.1007/s10957-010-9766-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10957-010-9766-2

Keywords

Navigation