Skip to main content
Log in

Some geometric results in semidefinite programming

  • Published:
Journal of Global Optimization Aims and scope Submit manuscript

Abstract

The purpose of this paper is to develop certain geometric results concerning the feasible regions of Semidefinite Programs, called hereSpectrahedra.

We first develop a characterization for the faces of spectrahedra. More specifically, given a pointx in a spectrahedron, we derive an expression for the minimal face containingx. Among other things, this is shown to yield characterizations for extreme points and extreme rays of spectrahedra. We then introduce the notion of an algebraic polar of a spectrahedron, and present its relation to the usual geometric polar.

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. F. Alizadeh (1991), Combinatorial Optimization with Interior Point Methods and Semi-Definite Matrices, Ph.D. Thesis, Computer Science Department, University of Minnesota, Minneapolis, Minnesota, 1991.

    Google Scholar 

  2. F. Alizadeh (1995), Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization,SIAM J. Optimization 5, No. 1.

    Google Scholar 

  3. G. P. Barker and D. Carlson (1975), Cones of Diagonally Dominant Matrices,Pac. J. Math. 57, 15–31.

    Google Scholar 

  4. P. Binding (1990), Simultaneous Diagonalization of Several Hermitian Matrices,SIAM J. Matrix Anal Appl. 11, 531–536.

    Google Scholar 

  5. P. Binding and C.-K. Li (1991), Joint Ranges of Hermitian Matrices and Simultaneous Diagonalization,Linear Algebra Appl. 151, 157–167.

    Google Scholar 

  6. A. Ben-Israel, A. Charnes, and K. Kortanek, (1969) Duality and Asymptotic Solvability over Cones,Bull. of AMS 75, 318–324.

    Google Scholar 

  7. A. Berman (1973),Cone, Matrices, and Mathematical Programming; Lecture Notes in Economics and Mathematical Systems, Springer.

  8. J. Borwein and H. Wolkowicz (1981), Characterization of Optimality for the Abstract Convex Program with Finite Dimensional Range,J. Austral. Math. Soc., Series A30, 390–411.

    Google Scholar 

  9. J. Cullum, W. E. Donath, and P. Wolfe (1975), The Minimization of Certain Nondifferentiable Sums of Eigenvalue Problems,Math. Prog. Study 3, 35–55.

    Google Scholar 

  10. C. Delorme and S. Poljak (1993), Combinatorial Properties and the Complexity of a Max-Cut Approximation,Europ. J. Combinatorics 14, 313–333.

    Google Scholar 

  11. R. Fletcher (1985), Semi-Definite Matrix Constraints in Optimization,SIAM J. Control and Optimization 23, 493–513.

    Google Scholar 

  12. M. X. Goemans and D. P. Williamson (1995), Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming,Submitted to J. ACM. (contact goemans@math.mit.edu for copies)

  13. R. Grone, S. Pierce, and W. Watkins (1990), Extremal Correlation Matrices,Linear Algebra and its Applications 134, pp. 63–70.

    Google Scholar 

  14. M. Grötschel, L. Lovásza, and A. Schrijver (1984), Polynomial Algorithms for Perfect Graphs,Annals of Discrete Mathematics 21, C. Berge and V. Chvátal, eds., North Holland.

  15. M. Grötschel, L. Lovász, and A. Schrijver (1988),Geometric Algorithms and Combinatorial Optimization, Springer-Verlag, Berlin.

    Google Scholar 

  16. R. Horn and C.R. Johnson,Matrix Analysis, Cambridge University Press, Cambridge, 1985.

    Google Scholar 

  17. M. Kojima, S. Kojima, and S. Hara, Linear Algebra for Semidefinite Programming, TR B-290, Research Reports on Information Sciences, Tokyo Institute of Technology, Tokyo, Japan, 1994.

    Google Scholar 

  18. M. Laurent and S. Poljak, On a Positive Semideflnite Relaxation of the Cut Polytope, Technical Report, LIENS-93-27, Ecole Normale Supérieure, France, 1993. (Contact monique@cwi.nl for copies)

    Google Scholar 

  19. L. Lovász and A. Schrijver, Cones of Matrices and Setfunctions, and 0–1 Optimization,SIAM J. Optimization 1 (1991).

  20. Y. Nesterov and A. Nemirovskii,Interior Point Polynomial Methods for Convex Programming: Theory and Applications, SIAM, 1994.

  21. M. L. Overton, Large-Scale Optimization of Eigenvalues,SIAM J. Optimization 2 (1992), pp. 88–120.

    Google Scholar 

  22. M. L. Overton and R. S. Womersley, Optimality Conditions and Duality Theory for Minimizing Sums of the Largest Eigenvalues of Symmetric Matrices,Math. Prog., Series B62 (1993), pp. 321–357.

    Google Scholar 

  23. P. M. Pardalos and S. A. Vavasis (1992), Open Questions in Complexity Theory for Numerical Optimization,Math. Prog. 57(2), 337–339.

    Google Scholar 

  24. G. Pataki, Algorithms for Linear Programs over Cones and Semidefinite Programming, Technical Report, GSIA, Carnegie-Mellon University, Pittsburgh, 1993. (contact gabor@magrathea.gsia.cmu.edu for copies)

    Google Scholar 

  25. G. Pataki, On the Facial Structure of Cone-LP's and Semidefinite Programs, Management Science Research Report # MSRR-595, GSIA, Carnegie-Mellon University, Pittsburgh, 1994.

    Google Scholar 

  26. M. Ramana (1995), An Exact Duality Theory for Semidefinite Programming and its Complexity Implications, DIMACS TR 95-02R (http://www.dimacs.edu), Rutgers University; Submitted toMath Programming.

  27. M. V. Ramana (1993), An algorithmic analysis of multiquadratic and Semidefinite programming problems, Ph.D. Thesis, The Johns Hopkins University, Baltimore, 1993.

    Google Scholar 

  28. M. V. Ramana and A. J. Goldman, Cutting Plane Techniques for Multiquadratic Programming, Under Preparation.

  29. M. V. Ramana and A. J. Goldman, Quadratic Maps with Convex Images, Submitted to Math of OR.

  30. T. R. Rockafellar,Convex Analysis, Princeton University Press, Princeton, 1970.

    Google Scholar 

  31. L. Vandenberghe and S. Boyd (1994), Positive-Definite Programming,Mathematical Programming: State of the Art 1994, J. R. Birge and K. G. Murty (eds.), U. of Michigan.

  32. H. Wolkowicz, Some Applications of Optimization in Matrix Theory,Linear Algebra and its Applications 40 (1981), 101–118.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Support received under the grants: NSF-STC91-19999 (DIMACS) and Air Force grant F49620-93-1-0041 (RUTCOR).

Support from the NSF grant ECS-9111548 is acknowledged.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ramana, M., Goldman, A.J. Some geometric results in semidefinite programming. J Glob Optim 7, 33–50 (1995). https://doi.org/10.1007/BF01100204

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01100204

Key words

Navigation