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Stationary Points of Bound Constrained Minimization Reformulations of Complementarity Problems

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  • M. V. Solodov

    (Institute de Matemática Pura e Aplicada)

Abstract

We consider two merit functions which can be used for solving the nonlinear complementarity problem via nonnegatively constrained minimization. One of the functions is the restricted implicit Lagrangian (Refs. 1–3), and the other appears to be new. We study the conditions under which a stationary point of the minimization problem is guaranteed to be a solution of the underlying complementarity problem. It appears that, for both formulations, the same regularity condition is needed. This condition is closely related to the one used in Ref. 4 for unrestricted implicit Lagrangian. Some new sufficient conditions are also given.

Suggested Citation

  • M. V. Solodov, 1997. "Stationary Points of Bound Constrained Minimization Reformulations of Complementarity Problems," Journal of Optimization Theory and Applications, Springer, vol. 94(2), pages 449-467, August.
  • Handle: RePEc:spr:joptap:v:94:y:1997:i:2:d:10.1023_a:1022695931376
    DOI: 10.1023/A:1022695931376
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    References listed on IDEAS

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    1. Z.-Q. Luo & O. L. Mangasarian & J. Ren & M. V. Solodov, 1994. "New Error Bounds for the Linear Complementarity Problem," Mathematics of Operations Research, INFORMS, vol. 19(4), pages 880-892, November.
    2. M. Seetharama Gowda & Jong-Shi Pang, 1992. "On Solution Stability of the Linear Complementarity Problem," Mathematics of Operations Research, INFORMS, vol. 17(1), pages 77-83, February.
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    Cited by:

    1. Immanuel Bomze & Werner Schachinger & Gabriele Uchida, 2012. "Think co(mpletely)positive ! Matrix properties, examples and a clustered bibliography on copositive optimization," Journal of Global Optimization, Springer, vol. 52(3), pages 423-445, March.
    2. N. Yamashita, 1998. "Properties of Restricted NCP Functions for Nonlinear Complementarity Problems," Journal of Optimization Theory and Applications, Springer, vol. 98(3), pages 701-717, September.

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