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On a Box-Constrained Linear Symmetric Cone Optimization Problem

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Abstract

In this paper, an analytical expression of the optimal solution for a box-constrained linear symmetric cone optimization problem is proposed. The resulting theories are established based on the theory of the spectral decomposition of a symmetric cone. Moreover, we apply our results to develop algorithms for solving several symmetric cone optimization problems and conduct some preliminary numerical experiments to show the performance of the developed algorithms.

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References

  1. Helmberg, C., Rendl, F., Vanderbei, R.J., Wolkowicz, H.: An interior-point method for semidefinite programming. SIAM J. Optim. 6, 342–361 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  2. Wolkowicz, H., Saigal, R., Vandenberghe, L.: Handbook of Semidefinite Programming: Theory, Algorithms, and Applications. Kluwer Academic Publishers, Dordrecht (2000)

    Book  MATH  Google Scholar 

  3. Ye, Y.Y.: Interior Point Algorithm: Theory and Analysis, Wiley-Interscience Series in Discrete Mathematics and Optimization. John Wiley and Sons, New York (1997)

    Book  Google Scholar 

  4. Jarre, F., Rendl, F.: An augmented primal-dual method for linear conic programs. SIAM J. Optim. 19, 808–823 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  5. Malick, J., Povh, J., Rendl, F., Wiegele, A.: Regularization methods for semidefinite programming. SIAM J. Optim. 20, 336–356 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  6. Toh, K.C.: An inexact primal-dual path-following algorithm for convex quadratic SDP. Math. Program. 112, 221–254 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  7. Zhao, X., Sun, D., Toh, K.: A Newton-CG augmented Lagrangian method for semidefinite programming. SIAM J. Optim. 20, 1737–1765 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  8. Xu, Y., Sun, W., Qi, L.: A feasible direction method for the semidefinite program with box constraints. Appl. Math. Lett. 24, 1874–1881 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  9. Birgin, E.G., Martinez, J.M.: Large-scale active-set box-constrained optimization method with spectral projected gradients. Comput. Optim. Appl. 23, 101–125 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  10. Dennis, J.E., Vicente, L.N.: Trust region interior point algorithms for minimization problems with simple bounds. In: Fisher, H., Riedmüler, B., Schäfler, S. (eds.) Applied Mathematics and Parallel Computing. Festschrift for Klaus Ritter, pp. 97–107. Springer, Berlin (1996)

    Chapter  Google Scholar 

  11. Facchinei, F., Júice, J., Soares, J.: An active set Newton’s algorithm for large-scale nonlinear programs with box constraints. SIAM J. Optim. 8, 158–186 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  12. Friedlander, A., Martinez, J.M., Santos, S.A.: A new trust region algorithm for bound constrained minimization. Appl. Math. Optim. 30, 235–266 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  13. Hager, W.W., Zhang, H.: Recent advances in bound constrained optimization. IFIP Int. Fed. Inf. Process. 199, 67–82 (2006)

    MathSciNet  MATH  Google Scholar 

  14. Alizadeh, F., Goldfarb, D.: Second-order cone programming. Math. Program. 95, 3–51 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  15. Faraut, J., Korányi, A.: Analysis on Symmetric Cones. Oxford Mathematical Monographs. Oxford University Press, New York (1994)

    MATH  Google Scholar 

  16. Nesterov, Y.E., Todd, M.J.: Self-scaled barriers and interior-point methods for convex programming. Math. Oper. Res. 22, 1–42 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  17. Schmieta, S.H., Alizadeh, F.: Extension of primal-dual interior point algorithms to symmetric cones. Math. Program. 96, 409–438 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  18. Sturm, J.F.: Similarity and other spectral relations for symmetric cones. Linear. Algebra. Appl. 312, 135–154 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  19. Broyden, C.G.: The convergence of a class of double-rank minimization algorithms. J. Inst. Math. Appl. 6, 76–90 (1970)

    Article  MATH  Google Scholar 

  20. Fletcher, R.: A new approach to variable metric algorithms. Comput. J. 13, 317–322 (1970)

    Article  MATH  Google Scholar 

  21. Löfberg, J.: YALMIP: A toolbox for modeling and optimization in MATLAB. In: Proceedings of the CACSD Conference, Taipei, Taiwan (2004)

  22. Tutuncu, R.H., Toh, K.C., Todd, M.J.: Solving semidefinite-quadratic-linear programs using SDPT3. Math. Program. 95, 189–217 (2003)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

Yi Xu was supported in part by the National Natural Science Foundation of China (No. 11501100, 11571178, 11671082 and 11871149). Xihong Yan was supported in part by the STIP of Higher Education Institutions in Shanxi (No. 201802103).

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Xu, Y., Yan, X. On a Box-Constrained Linear Symmetric Cone Optimization Problem. J Optim Theory Appl 181, 946–971 (2019). https://doi.org/10.1007/s10957-019-01493-z

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  • DOI: https://doi.org/10.1007/s10957-019-01493-z

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