Skip to main content
Log in

New approximations for the cone of copositive matrices and its dual

  • Full Length Paper
  • Series A
  • Published:
Mathematical Programming Submit manuscript

Abstract

We provide convergent hierarchies for the convex cone \(\mathcal{C }\) of copositive matrices and its dual \(\mathcal{C }^*\), the cone of completely positive matrices. In both cases the corresponding hierarchy consists of nested spectrahedra and provide outer (resp. inner) approximations for \(\mathcal{C }\) (resp. for its dual \(\mathcal{C }^*\)), thus complementing previous inner (resp. outer) approximations for \(\mathcal{C }\) (for \(\mathcal{C }^*\)). In particular, both inner and outer approximations have a very simple interpretation. Finally, extension to \(\mathcal{K }\)-copositivity and \(\mathcal{K }\)-complete positivity for a closed convex cone \(\mathcal{K }\), is straightforward.

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.

Fig. 1

Similar content being viewed by others

References

  1. Anstreicher, K.M., Burer, S.: Computable representations for convex hulls of low-dimensional quadratic forms. Math. Program. Sér. B 124, 33–43 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  2. Bomze, I.M.: Copositive optimization—recent developments and applications. Eur. J. Oper. Res. 216, 509–520 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  3. Bomze, I.M., Schachinger, W., Uchida, G.: Think co(mpletely) positive!—matrix properties, examples and a clustered bibliography on copositive optimization. J. Glob. Optim. 52, 423–445 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  4. Bomze, I.M., de Klerk, E.: Solving standard quadratic optimization problems via linear, semidenite and copositive programming. J. Glob. Optim. 24, 163–185 (2002)

    Article  MATH  Google Scholar 

  5. Burer, S.: Copositive programming. In: Anjos, M., Lasserre, J.B. (eds.) Handbook of Semidefinite, Conic and Polynomial Optimization, pp. 201–218. Springer, New York (2012)

  6. de Klerk, E., Pasechnik, D.V.: A linear programming formulation of the standard quadratic optimization problem. J. Glob. Optim. 37, 75–84 (2007)

    Article  MATH  Google Scholar 

  7. de Klerk, E., Pasechnik, D.V.: Approximation of the stability number of a graph via copositive programming. SIAM J. Optim. 12, 875–892 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  8. Dür, M.: Copositive programming —a survey. In: Diehl, M., Glineur, F., Jarlebring, E., Michiels, W. (eds.) Recent Advances in Optimization and its Applications in Engineering, pp. 3–20. Springer, New York (2010)

  9. Gaddum, J.W.: Linear inequalities and quadratic forms. Pacific J. Math. 8, 411–414 (1958)

    Article  MATH  MathSciNet  Google Scholar 

  10. Grundmann, A., Moeller, H.M.: Invariant integration formulas for the n-simplex by combinatorial methods. SIAM J. Numer. Anal. 15, 282–290 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  11. Hiriart-Urruty, J.-B., Seeger, A.: A variational approach to copositive matrices. SIAM Rev. 52, 593–629 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  12. Lasserre, J.B.: A new look at nonnegativity and polynomial optimization. SIAM J. Optim. 21, 864–885 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  13. Parrilo, P.: Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization. Ph.D. Dissertation, California Institute of Technology (2000)

  14. Peña, J., Vera, J., Zuluaga, L.: Computing the stability number of a graph via linear and semidenite programming. SIAM J. Optim. 18, 87–105 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  15. Rockafellar, R.T.: Convex Analysis. Princeton University Preess, Priceton, New Jersey (1970)

    MATH  Google Scholar 

  16. Schmüdgen, K.: The \(K\)-moment problem for compact semi-algebraic sets. Math. Ann. 289, 203–206 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  17. Schweighofer, M.: Global optimization of polynomials using gradient tentacles and sums of squares. SIAM J. Optim. 17, 920–942 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  18. Stengel, G.: A Nullstellensatz and a Positivstellensatz in semialgebraic geometry. Math. Ann. 207, 87–97 (1974)

    Google Scholar 

  19. Vandenberghe, L., Boyd, S.: Semidefinite programming. SIAM Rev. 38, 49–95 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  20. Yildirim, E.A.: On the accuracy of uniform polyhedral approximations of the copositive cone. Optim. Methods Softw. 27, 155–173 (2012)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgments

The author wishes to thank two anonymous referees for their very helpful remarks and suggestions to improve the initial version of this note.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jean B. Lasserre.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lasserre, J.B. New approximations for the cone of copositive matrices and its dual. Math. Program. 144, 265–276 (2014). https://doi.org/10.1007/s10107-013-0632-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10107-013-0632-5

Keywords

Mathematics Subject Classification (1991)

Navigation