Skip to main content
Log in

Global optimization of rational functions: a semidefinite programming approach

  • Published:
Mathematical Programming Submit manuscript

Abstract.

We consider the problem of global minimization of rational functions on (unconstrained case), and on an open, connected, semi-algebraic subset of , or the (partial) closure of such a set (constrained case). We show that in the univariate case (n = 1), these problems have exact reformulations as semidefinite programming (SDP) problems, by using reformulations introduced in the PhD thesis of Jibetean [16]. This extends the analogous results by Nesterov [13] for global minimization of univariate polynomials.

For the bivariate case (n = 2), we obtain a fully polynomial time approximation scheme (FPTAS) for the unconstrained problem, if an a priori lower bound on the infimum is known, by using results by De Klerk and Pasechnik [1].

For the NP-hard multivariate case, we discuss semidefinite programming-based relaxations for obtaining lower bounds on the infimum, by using results by Parrilo [15], and Lasserre [12].

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. de Klerk, E., Pasechnik, D. V.: Products of positive forms, linear matrix inequalities, and Hilbert 17-th problem for ternary forms. European J. of Operational Research, 157 (1), 39–45 (2004)

    Google Scholar 

  2. Drud, A.: CONOPT – a CRG code for large sparse dynamic nonlinear optimization problems. Mathematical Programming, 31, 153–191 (1985)

    MATH  MathSciNet  Google Scholar 

  3. Hanzon, B., Jibetean, D.: Global minimization of a multivariate polynomial using matrix methods. Global Optimization, 27 (1), 1–23 (2003)

    Article  MathSciNet  Google Scholar 

  4. Henrion, D., Lasserre, J.: Gloptipoly: Global optimization over polynomials with Matlab and SeDuMi. ACM Transactions on Mathematical Software, 29 (2), 165–194, (2003)

    Article  MathSciNet  Google Scholar 

  5. Jibetean, D.: Global optimization of rational multivariate functions. Technical Report PNA-R0120, CWI, Amsterdam, 2001

  6. Jibetean, D.: Algebraic optimization with applications to system theory. PhD thesis, Vrije Universiteit, Amsterdam, 2003. Available from http://www.math.vu.nl/research/theses/jibetean.php.

  7. Jibetean, D., Hanzon, B.: Linear matrix inequalities for global optimization of rational functions and H 2 optimal model reduction. In: Gilliam, D., Rosenthal, J. (eds), Proc. of the 15th International Symposium on MTNS, 2002

  8. Kojima, M., Tunçel, L.: Cones of matrices and successive convex relaxations of nonconvex sets. SIAM J. Optimization, 10, 750–778 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  9. Kojima, M., Tunçel, L.: Discretization and localization in successive convex relaxation methods for nonconvex quadratic optimization problems. Mathematical Programming, Series A, 89, 79–111 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  10. Lam, T.: An introduction to real algebra. Rocky Mountain J. Math. 14 (4), 767–814 (1984)

    Article  MathSciNet  Google Scholar 

  11. Lassere, J.: Global optimization with polynomials and the problem of moments. SIAM J.Optim. 11 (3), 796–817 (2001)

    Article  Google Scholar 

  12. Lasserre, J.: Global optimization with polynomials and the problem of moments. SIAM J. Optimization, 11, 296–817 (2001)

    MathSciNet  Google Scholar 

  13. Nesterov, Y.: Squared functional systems and optimization problems. In: Frenk, H., Roos, K., Terlaky, T., Zhang, S. (eds), High performance optimization, pages 405–440. Kluwer Academic Publishers, 2000

  14. Parillo, P.: Structured Semidefinite Programs and Semi-algebraic Geometry Methods in Robustness and Optimization. PhD thesis, California Institute of Technology, Pasadena, California, USA, 2000. Available from http://www.cds.caltech.edu/~pablo/.

  15. Parrilo, P. A.: Semidefinite programming relaxations for semialgebraic problems. Mathematical Programming Ser. B, 96 (2), 293–320 (2003)

    Article  MathSciNet  Google Scholar 

  16. Parrilo, P. A., Sturmfels, B.: Minimizing polynomial functions. In: Algorithmic and quantitative real algebraic geometry, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, AMS, Vol. 60, 83–99 (2003)

    MATH  MathSciNet  Google Scholar 

  17. Powers, V., Reznick, B.: Polynomials that are positive on an interval. Trans. Amer. Math. Soc. 352, 4677–4692 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  18. Prajna, S., Papachristodoulou, A., Parrilo, P. A.: SOSTOOLS: Sum of squares optimization toolbox for MATLAB, 2004. Available from http://www.cds.caltech.edu/sostools

  19. Putinar, M.: Positive polynomials on compact semi-algebraic sets. Ind. Univ. Math. J. 42, 969–984 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  20. Reznick, B.: Uniform denominators in Hilbert's seventeenth problem. Math. Z. 220 (1), 75–97 (1995)

    MathSciNet  Google Scholar 

  21. Reznick, B.: Some concrete aspects of Hilbert's 17th Problem. In: Real algebraic geometry and ordered structures (Baton Rouge, LA, 1996), pages 251–272. Amer. Math. Soc., Providence, RI, 2000

  22. Schmüdgen, K.: The k-moment problem for compact semi-algebraic sets. Math. Ann. 2, 203–206 (1991)

    Article  MATH  Google Scholar 

  23. Sturmfels, B.: Solving Systems of Polynomial Equations. Number 97 in CBMS Regional Conference Series in Mathematics. American Mathematical Society, 2002

  24. Takeda, A., Dai, Y., Fukuda, M., Kojima, M.: Towards implementations of successive convex relaxation methods for nonconvex quadratic optimization problems. In: Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems, pages 489–510. Kluwer Academic Publishers, 2000

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. Jibetean.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jibetean, D., de Klerk, E. Global optimization of rational functions: a semidefinite programming approach. Math. Program. 106, 93–109 (2006). https://doi.org/10.1007/s10107-005-0589-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10107-005-0589-0

Mathematics Subject Classification (2000):

Navigation