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Foundations of Set-Semidefinite Optimization

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Book cover Nonlinear Analysis and Variational Problems

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 35))

Abstract

In this paper, we present various foundations of a new field of research in optimization unifying semidefinite and copositive programming, which is called set-semidefinite optimization. A set-semidefinite optimization problem is a vector optimization problem with a special constraint defined by a so-called set-semidefinite ordering cone. The investigations of this chapter are based on the paper [11].

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References

  1. L.-F. Andersson, G. Chang and T. Elfving, “Criteria for copositive matrices using simplices and barycentric coordinates”, Linear Algebra Appl. 220 (1995) 9–30.

    Article  MATH  MathSciNet  Google Scholar 

  2. I.M.Bomze and E.de Klerk, “Solving standard quadratic optimization problems via linear, semidefinite and copositive programming”, J. Global Optim. 24 (2002) 163–185.

    Article  MATH  MathSciNet  Google Scholar 

  3. I.M. Bomze, M. Dür, E. de Klerk, C. Roos, A.J. Quist and T. Terlaky, “On copositive programming and standard quadratic optimization problems”, J. Global Optim. 18 (2000) 301–320.

    Article  MATH  MathSciNet  Google Scholar 

  4. J.M. Borwein, “Necessary and sufficient conditions for quadratic minimality”, Numerical Funct. Anal. Optimization 5 (1982) 127–140.

    Article  MATH  Google Scholar 

  5. S. Bundfuss and M. Dür, “Criteria for copositivity and approximations of the copositive cone” (Preprint, Department of Mathematics, Darmstadt University of Technology, Darmstadt, 2006).

    Google Scholar 

  6. S. Bundfuss and M. Dür, “Algorithmic Copositivity Detection by Simplicial Partition”, Linear Algebra Appl. 428 (2008) 1511–1523.

    Article  MATH  MathSciNet  Google Scholar 

  7. S. Burer, “On the copositive representation of binary and continuous nonconvex quadratic programs”, Math. Program. 120(2009)479-495 DOI 10.1007/s10107-008-0223-z.

    Google Scholar 

  8. G. Danninger, “Role of copositivity in optimality criteria for nonconvex optimization problems”, J. Optimization Theory Appl. 75 (1992) 535–558.

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  10. I. Dukanovic and F. Rendl, “Semidefinite programming relaxations for graph coloring and maximal clique problems”, Math. Program. 109(2) (2007) 345–365.

    Article  MATH  MathSciNet  Google Scholar 

  11. G. Eichfelder and J. Jahn, “Set-semidefinite optimization”, J. Convex Anal. 15 (2008) 767–801.

    MATH  MathSciNet  Google Scholar 

  12. M. Fukuda, M. Yamashita and M. Kojima, “Computational Prospects on Copositive Programming”, RIMS Kokyuroku 1526 (2006) 207–213.

    Google Scholar 

  13. M.X. Goemans, “Semidefinite programming in combinatorial optimization”, Math. Program. 79 (1997) 143–161.

    MathSciNet  MATH  Google Scholar 

  14. M.S. Gowda, “A characterization of positive semidefinite operators on a Hilbert space”, J. Optimization Theory Appl. 48 (1986) 419–425.

    Article  MATH  MathSciNet  Google Scholar 

  15. J. Jahn, Vector Optimization - Theory, Applications, and Extensions (Springer, Berlin, 2004).

    MATH  Google Scholar 

  16. J. Jahn, Introduction to the Theory of Nonlinear Optimization (Springer, Berlin, 2007).

    MATH  Google Scholar 

  17. J. Jahn, Int. J. Optimization: Theory, Methods and Appl. 1 (2009) 123-139.

    Google Scholar 

  18. W. Kaplan, “A test for copositive matrices”, Linear Algebra Appl. 313 (2000) 203–206.

    Article  MATH  MathSciNet  Google Scholar 

  19. W. Kaplan, “A copositivity probe”, Linear Algebra Appl. 337 (2001) 237–251.

    Article  MATH  MathSciNet  Google Scholar 

  20. K. Löwner, “über monotone Matrixfunktionen”, Math. Z. 38 (1934) 177–216.

    Article  MathSciNet  Google Scholar 

  21. H. Maurer and J. Zowe, “First and second-order necessary and sufficient optimality conditions for infinite-dimensional programming problems”, Math. Programming 16 (1979) 98–110.

    Article  MATH  MathSciNet  Google Scholar 

  22. P.M. Pardalos, M. Panos and J.E. Xue, “The maximum clique problem”, J. Global Optim. 4(3) (1994) 301-328

    Article  MATH  MathSciNet  Google Scholar 

  23. J. Povh and F. Rendl, “Copositive and semidefinite relaxations of the quadratic assignment problem” (manuscript, University of Maribor, Faculty of Logistics, Celje, Slovenia, 2006).

    Google Scholar 

  24. J. Povh and F. Rendl, “A copositive programming approach to graph partitioning”, SIAM J. Optimization 18 (2007) 223–241.

    Article  MATH  MathSciNet  Google Scholar 

  25. A.J. Quist, E. de Klerk, C. Roos and T. Terlaky, “Copositive relaxation for general quadratic programming”, Optim. Methods Softw. 9 (1998) 185–208.

    Article  MATH  MathSciNet  Google Scholar 

  26. J.F. Sturm and S. Zhang, “On cones of nonnegative quadratic functions”, Math. Oper. Res. 28 (2003) 246–267.

    Article  MATH  MathSciNet  Google Scholar 

  27. M.J. Todd, “Semidefinite optimization”, Acta Numerica 10 (2001) 515–560.

    Article  MATH  MathSciNet  Google Scholar 

  28. L. Vandenberghe and S. Boyd, “Semidefinite programming”, SIAM Rev. 38 (1996) 49–95.

    Article  MATH  MathSciNet  Google Scholar 

  29. L. Vandenberghe and S. Boyd, “Connections between semi-infinite and semidefinite programming”, in: R. Reemtsen and J.J. Rueckmann, Semi-Infinite Programming (Kluwer, Boston, 1998), p. 277–294.

    Google Scholar 

  30. L. Vandenberghe and S. Boyd, “Applications of semidefinite programming”, Appl. Numer. Math. 29(3) (1999) 283–299.

    Article  MATH  MathSciNet  Google Scholar 

  31. H. Wolkowicz, R. Saigal and L. Vandenberghe (eds.), Handbook on Semidefinite Programming (Kluwer, 2000).

    Google Scholar 

  32. H. Väliaho, “Quadratic-programming criteria for copositive matrices”, Linear Algebra Appl. 119 (1989) 163–182.

    Article  MATH  MathSciNet  Google Scholar 

  33. J. Werner, Optimization, Theory and Applications (Vieweg, Braunschweig, 1984).

    MATH  Google Scholar 

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Acknowledgment

The authors thank Prof. Constantin Zălinescu for valuable discussions.

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Correspondence to Gabriele Eichfelder .

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Dedicated to the memory of Professor George Isac

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Eichfelder, G., Jahn, J. (2010). Foundations of Set-Semidefinite Optimization. In: Pardalos, P., Rassias, T., Khan, A. (eds) Nonlinear Analysis and Variational Problems. Springer Optimization and Its Applications, vol 35. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0158-3_18

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