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Analysis of a non-interior continuation method for second-order cone programming

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Abstract

Based on the Chen-Harker-Kanzow-Smale (CHKS) smoothing function, a non-interior continuation method is presented for solving the second-order cone programming (SOCP). Our algorithm reformulates the SOCP as a nonlinear system of equations and then applies Newton’s method to the perturbation of this system. The proposed algorithm does not have restrictions regarding its starting point and solves at most one linear system of equations at each iteration. Under suitable assumptions, the algorithm is shown to be globally and locally quadratically convergent. Some numerical results are also included which indicate that our algorithm is promising and comparable to interior-point methods.

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References

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

    Article  MATH  MathSciNet  Google Scholar 

  2. Burke, J., Xu, S.: A non-interior predictor-corrector path following algorithm for the monotone linear complementarity problem. Math. Program. 87, 113–130 (2000)

    MATH  MathSciNet  Google Scholar 

  3. Chen, X., Qi, L., Sun, D.: Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities. Math. Comput. 67, 519–540 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  4. Chen, X.D., Sun, D., Sun, J.: Complementarity functions and numerical experiments on smoothing Newton methods for second-order-cone complementarity problems. Comput. Optim. Appl. 25, 39–56 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  5. Chen, X., Tseng, P.: Non-interior continuation methods for solving semidefinite complementarity problems. Math. Program. 95, 431–474 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  6. Chen, B., Xiu, N.: A global linear and local quadratic non-interior continuation method for nonlinear complementarity problems based on Chen-Mangasarian smoothing functions. SIAM J. Optim. 9, 605–623 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  7. Clarke, F.H.: Optimization and Nonsmooth Analysis. Wiley, New York (1983)

    MATH  Google Scholar 

  8. Engelke, S., Kanzow, C.: Improved smoothing-type methods for the solution of linear programs. Numer. Math. 90, 487–507 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  9. Engelke, S., Kanzow, C.: Predictor-corrector smoothing methods for linear programs with a more flexible update of the smoothing parameter. Comput. Optim. Appl. 23, 299–320 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  10. Faraut, J., Korányi, A.: Analysis on Symmetric Cones. Oxford University Press, Oxford (1994)

    MATH  Google Scholar 

  11. Fukushima, M., Luo, Z.Q., Tseng, P.: Smoothing functions for second-order-cone complementarity problems. SIAM J. Optim. 12, 436–460 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  12. Huang, Z.H., Han, J., Chen, Z.: A predictor-corrector smoothing Newton algorithm, based on a new smoothing function, for solving the nonlinear complementarity problems with a P 0 function. J. Optim. Theory Appl. 117, 39–68 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  13. Liu, Y.J., Zhang, L.W., Wang, Y.H.: Analysis of a smoothing method for symmetric conic linear programming. J. Appl. Math. Comput. 22, 133–148 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  14. Lobo, M.S., Vandenberghe, L., Boyd, S., Lebret, H.: Applications of second-order cone programming. Linear Algebra Appl. 284, 193–228 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  15. Mifflin, R.: Semismooth and semiconvex functions in constrained optimization. SIAM J. Control Optim. 15, 957–972 (1977)

    Article  MathSciNet  Google Scholar 

  16. Qi, L., Sun, J.: A nonsmooth version of Newton’s method. Math. Program. 58, 353–367 (1993)

    Article  MathSciNet  Google Scholar 

  17. Qi, L., Sun, D.: Improving the convergence of non-interior point algorithm for nonlinear complementarity problems. Math. Comput. 69, 283–304 (2000)

    MATH  MathSciNet  Google Scholar 

  18. Qi, L., Sun, D., Zhou, G.: A new look at smoothing Newton methods for nonlinear complementarity problems and box constrained variational inequalities. Math. Program. 87, 1–35 (2000)

    MATH  MathSciNet  Google Scholar 

  19. Sun, D., Sun, J.: Strong semismoothness of Fischer-Burmeister SDC and SOC complementarity functions. Math. Program. 103, 575–581 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  20. Toh, K.C., Tütüncü, R.H., Todd, M.J.: SDPT3 Version 3.02—a MATLAB software for semidefinite-quadratic-linear programming. http://www.math.nus.edu.sg/~mattohkc/sdpt3.html (2002)

  21. Tseng, P.: Analysis of a non-interior continuation method based on Chen-Mangasarian smoothing functions for complementarity problems. In: Fukushima, M., Qi, L. (eds.) Reformulation–Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, pp. 381–404. Kluwer Academic, Boston (1999)

    Google Scholar 

  22. Zhang, L.W., Liu, Y.J.: Convergence analysis of a nonlinear Lagrange algorithm for nonlinear programming with inequality constraints. J. Appl. Math. Comput. 13, 1–10 (2003)

    Article  MATH  MathSciNet  Google Scholar 

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Correspondence to Xiaoni Chi.

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This research was partially supported by the National Science Foundation of China (Grant No. 60574075, 60674108) and Cross-century Talent Award by the Ministry of Education, China.

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Chi, X., Liu, S. Analysis of a non-interior continuation method for second-order cone programming. J. Appl. Math. Comput. 27, 47–61 (2008). https://doi.org/10.1007/s12190-008-0057-0

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  • DOI: https://doi.org/10.1007/s12190-008-0057-0

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