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First and second order analysis of nonlinear semidefinite programs

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Abstract

In this paper we study nonlinear semidefinite programming problems. Convexity, duality and first-order optimality conditions for such problems are presented. A second-order analysis is also given. Second-order necessary and sufficient optimality conditions are derived. Finally, sensitivity analysis of such programs is discussed.

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References

  1. F. Alizadeh, Combinatorial optimization with interior point methods and semi-definite matrices, Ph.D. Thesis, University of Minnesota, 1991.

  2. F. Alizadeh, J.-P.A. Haeberly and M.L. Overton, Primal-dual interior-point methods for semidefinite programming, preprint, presented at theXV Symposium on Mathematical Programming, Ann Arbor, 1994.

  3. F. Alizadeh, J.-P.A. Haeberly and M.L. Overton, Complementarity and nondegeneracy in semidefinite programming,Mathematical Programming 77 (1997) 111–128 (this issue).

    Article  MathSciNet  Google Scholar 

  4. V.I. Arnold, On matrices depending on parameters,Russian Mathematical Surveys 26 (1971) 29–43.

    Article  Google Scholar 

  5. J.F. Bonnans, R. Cominetti and A. Shapiro, Second order necessary and sufficient optimality conditions under abstract constraints, Preprint.

  6. M.W. Browne, Generalized least squares estimators in the analysis of covariance structures,South African Statistical Journal 8 (1974) 1–24.

    MathSciNet  Google Scholar 

  7. R. Cominetti, Metric regularity, tangent sets and second order optimality conditions,Applied Mathematics and Optimization 21 (1990) 265–287.

    Article  MATH  MathSciNet  Google Scholar 

  8. A.V. Fiacco,Introduction to Sensitivity and Stability Analysis in Nonlinear Programming (Academic Press, New York, 1983).

    MATH  Google Scholar 

  9. E.G. Gol’shtein,Theory of Convex Programming, Translations of Mathematical Monographs, Vol. 36 (American Mathematical Society, Providence, RI, 1972).

    Google Scholar 

  10. M. Golubitsky and V. Guillemin,Stable Mappings and Their Singularities (Springer, New York, 1973).

    MATH  Google Scholar 

  11. R.A. Horn and C.R. Johnson,Topics in Matrix Analysis (Cambridge University Press, Cambridge, 1991).

    MATH  Google Scholar 

  12. H. Kawasaki, An envelope-like effect of infinitely many inequality constraints on second order necessary conditions for minimization problems,Mathematical Programming 41 (1988) 73–96.

    Article  MATH  MathSciNet  Google Scholar 

  13. S. Kurcyusz, On the existence and nonexistence of Lagrange multipliers in Banach spaces,Journal of Optimization Theory and Applications 20 (1976) 81–110.

    Article  MATH  MathSciNet  Google Scholar 

  14. P. Lancaster, On eigenvalues of matrices dependent on a parameter,Numerische Mathematik 6 (1964) 377–387.

    Article  MATH  MathSciNet  Google Scholar 

  15. A.W. Marshall and I. Olkin,Inequalities: Theory of Majorization and Its Applications (Academic Press, New York, 1979).

    MATH  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  17. Y.E. Nesterov and A.S. Nemirovskii,Interior Point Polynomial Algorithms in Convex Programming, SIAM Studies in Applied Mathematics (SIAM, Philadelphia, PA, 1994).

    MATH  Google Scholar 

  18. M.L. Overton and R.S. Womersley, Second derivatives for optimizing eigenvalues of symmetric matrices,SIAM Journal on Matrix Analysis and Applications 16 (1995) 697–718.

    Article  MATH  MathSciNet  Google Scholar 

  19. G. Pataki, On the multiplicity of optimal eigenvalues, Management Science Research Report #MSRR-604, GSIA, Carnegie Mellon University.

  20. J.P. Penot, On regularity conditions in mathematical programming,Mathematical Programming Study 19 (1982) 167–199.

    MATH  MathSciNet  Google Scholar 

  21. S.M. Robinson, First order conditions for general nonlinear optimization,SIAM Journal on Applied Mathematics 30 (1976) 597–607.

    Article  MATH  MathSciNet  Google Scholar 

  22. R.T. Rockafellar,Convex Analysis (Princeton University Press, Princeton, NJ, 1970).

    MATH  Google Scholar 

  23. R.T. Rockafellar,Conjugate Duality and Optimization, Regional Conference Series in Applied Mathematics (SIAM, Philadelphia, PA, 1974).

    MATH  Google Scholar 

  24. R.Y. Rubinstein and A. Shapiro,Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method (John Wiley and Sons, New York, NY, 1993).

    MATH  Google Scholar 

  25. A. Shapiro, Rank-reducibility of a symmetric matrix and sampling theory of minimum trace factor analysis,Psychometrika 47 (1982) 187–199.

    Article  MATH  MathSciNet  Google Scholar 

  26. A. Shapiro, On the unsolvability of inverse eigenvalue problems almost everywhere,Linear Algebra and Its Applications 49 (1983) 27–31.

    Article  MATH  MathSciNet  Google Scholar 

  27. A. Shapiro, Extremal problems on the set of nonnegative definite matrices,Linear Algebra and Its Applications 67 (1985) 7–18.

    Article  MATH  MathSciNet  Google Scholar 

  28. A. Shapiro, Perturbation theory of nonlinear programs when the set of optimal solutions is not a singleton,Applied Mathematics and Optimization 18 (1988) 215–229.

    Article  MATH  MathSciNet  Google Scholar 

  29. A. Shapiro, Sensitivity analysis of nonlinear programs and differentiability properties of metric projections,SIAM J. Control and Optimization 26 (1988) 628–645.

    Article  MATH  MathSciNet  Google Scholar 

  30. A. Shapiro and M.K.H. Fan, On eigenvalue optimization,SIAM J. on Optimization 5 (1995) 552–569.

    Article  MATH  MathSciNet  Google Scholar 

  31. A. Shapiro, Directional differentiability of the optimal value function in convex semi-infinite programming,Mathematical Programming 70 (1995) 149–157.

    MathSciNet  Google Scholar 

  32. A. Shapiro, On uniqueness of Lagrange multipliers in optimization problems subject to cone constraints,SIAM J. on Optimization, to appear.

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Shapiro, A. First and second order analysis of nonlinear semidefinite programs. Mathematical Programming 77, 301–320 (1997). https://doi.org/10.1007/BF02614439

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