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A New Class of Semismooth Newton-Type Methods for Nonlinear Complementarity Problems

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Abstract

We introduce a new, one-parametric class of NCP-functions. This class subsumes the Fischer function and reduces to the minimum function in a limiting case of the parameter. This new class of NCP-functions is used in order to reformulate the nonlinear complementarity problem as a nonsmooth system of equations. We present a detailed investigation of the properties of the equation operator, of the corresponding merit function as well as of a suitable semismooth Newton-type method. Finally, numerical results are presented for this method being applied to a number of test problems.

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References

  1. S.C. Billups, Algorithms for Complementarity Problems and Generalized Equations, Ph.D. Thesis, Computer Sciences Department, University of Wisconsin, Madison, WI, 1995.

    Google Scholar 

  2. F.H. Clarke, Optimization and Nonsmooth Analysis, John Wiley & Sons: New York, NY, 1983 (reprinted by SIAM, Philadelphia, PA, 1990).

    Google Scholar 

  3. R.W. Cottle, J.-S. Pang, and R.E. Stone, The Linear Complementarity Problem, Academic Press: Boston, 1992.

    Google Scholar 

  4. T. De Luca, F. Facchinei, and C. Kanzow, “A semismooth equation approach to the solution of nonlinear complementarity problems,” Mathematical Programming, vol. 75, pp. 407-439, 1996.

    Google Scholar 

  5. S.P. Dirkse and M.C. Ferris, “MCPLIB: A collection of nonlinear mixed complementarity problems,” Optimization Methods and Software, vol. 5, pp. 123-156, 1995.

    Google Scholar 

  6. F. Facchinei, A. Fischer, and C. Kanzow, “Inexact Newton methods for semismooth equations with applications to variational inequality problems,” in Nonlinear Optimization and Applications, G. Di Pillo and F. Giannessi (Eds.), Plenum Press: New York, NY, 1996, pp. 125-139.

    Google Scholar 

  7. F. Facchinei, A. Fischer, and C. Kanzow, “A semismooth Newton method for variational inequalities: The case of box constraints,” in Complementarity and Variational Problems, State of the Art, M.C. Ferris and J.-S. Pang (Eds.), SIAM: Philadelphia, PA, pp. 76-90.

  8. F. Facchinei and J. Soares, “A new merit function for nonlinear complementarity problems and a related algorithm,” SIAM Journal on Optimization, vol. 7, pp. 225-247, 1997.

    Google Scholar 

  9. M.C. Ferris, Private communication, September 1996.

  10. M.C. Ferris and C. Kanzow, “Recent developments in the solution of nonlinear complementarity problems,” Preprint, in preparation.

  11. M.C. Ferris and J.-S. Pang, “Engineering and economic applications of complementarity problems,” SIAM Review, vol. 39, pp. 669-713, 1997.

    Google Scholar 

  12. M.C. Ferris and T.F. Rutherford, “Accessing realistic mixed complementarity problems within MATLAB,” in Nonlinear Optimization and Applications, G. Di Pillo and F. Giannessi (Eds.), Plenum Press: New York, NY, pp. 141-153.

  13. A. Fischer, “A special Newton-type optimization method,” Optimization, vol. 24, pp. 269-284, 1992.

    Google Scholar 

  14. A. Fischer, “Solution of monotone complementarity problems with locally Lipschitzian functions,” Mathematical Programming, vol. 76, pp. 513-532, 1997.

    Google Scholar 

  15. A. Fischer and C. Kanzow, “On finite termination of an iterative method for linear complementarity problems,” Mathematical Programming, vol. 74, pp. 279-292, 1996.

    Google Scholar 

  16. S.A. Gabriel and J.J. Moré, “Smoothing of mixed complementarity problems,” in Complementarity and Variational Problems, State of the Art, M.C. Ferris and J.-S. Pang (Eds.), SIAM: Philadelphia, PA, pp. 105-116.

  17. L. Grippo, F. Lampariello, and S. Lucidi, “A nonmonotone linesearch technique for Newton's method,” SIAM Journal on Numerical Analysis, vol. 23, pp. 707-716, 1986.

    Google Scholar 

  18. C. Kanzow, “Semismooth newton-type methods for the solution of nonlinear complementarity problems,” Habilitation Thesis, Institute of Applied Mathematics, University of Hamburg, Hamburg, April 1997.

    Google Scholar 

  19. C. Kanzow and M. Fukushima, “Equivalence of the generalized complementarity problem to differentiable unconstrained minimization,” Journal of Optimization Theory and Applications, vol. 90, pp. 581-603, 1996.

    Google Scholar 

  20. B. Kummer, “Newton's method for non-differentiable functions,” in Mathematical Research, Advances in Mathematical Optimization, J. Guddat et al. (Eds.), Akademie-Verlag: Berlin, Germany, 1988, pp. 114-125.

    Google Scholar 

  21. R. Mifflin, “Semismooth and semiconvex functions in constrained optimization,” SIAM Journal on Control and Optimization, vol. 15, pp. 957-972, 1977.

    Google Scholar 

  22. J.J. Moré and W.C. Rheinboldt, “On P-and S-functions and related classes of n-dimensional nonlinear mappings,” Linear Algebra and its Applications, vol. 6, pp. 45-68, 1973.

    Google Scholar 

  23. J.-S. Pang, “Newton's method for B-differentiable equations,” Mathematics of Operations Research, vol. 15, pp. 311-341, 1990.

    Google Scholar 

  24. J.-S. Pang, “A B-differentiable equation-based, globally and locally quadratically convergent algorithm for nonlinear programs, complementarity and variational inequality problems,” Mathematical Programming, vol. 51, pp. 101-131, 1991.

    Google Scholar 

  25. J.-S. Pang and L. Qi, “Nonsmooth equations: Motivation and algorithms,” SIAM Journal on Optimization, vol. 3, pp. 443-465, 1993.

    Google Scholar 

  26. L. Qi, “Convergence analysis of some algorithms for solving nonsmooth equations,” Mathematics of Operations Research, vol. 18, pp. 227-244, 1993.

    Google Scholar 

  27. L. Qi and J. Sun, “A nonsmooth version of Newton's method,” Mathematical Programming, vol. 58, pp. 353-367, 1993.

    Google Scholar 

  28. S.M. Robinson, “Strongly regular generalized equations,”Mathematics of Operations Research, vol. 5, pp. 43-62, 1980.

    Google Scholar 

  29. Ph.L. Toint, “Non-monotone trust-region algorithms for nonlinear optimization subject to convex constraints,” Mathematical Programming, vol. 77, pp. 69-94, 1997.

    Google Scholar 

  30. P. Tseng, “Growth behaviour of a class of merit functions for the nonlinear complementarity problem,” Journal of Optimization Theory and Applications, vol. 89, pp. 17-37, 1996.

    Google Scholar 

  31. N. Yamashita and M. Fukushima, “Modified Newton methods for solving a semismooth reformulation of monotone complementarity problems,” Mathematical Programming, vol. 76, pp. 469-491, 1997.

    Google Scholar 

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Kanzow, C., Kleinmichel, H. A New Class of Semismooth Newton-Type Methods for Nonlinear Complementarity Problems. Computational Optimization and Applications 11, 227–251 (1998). https://doi.org/10.1023/A:1026424918464

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