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A Globally Convergent Smoothing Newton Method for Nonsmooth Equations and Its Application to Complementarity Problems

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Abstract

The complementarity problem is theoretically and practically useful, and has been used to study and formulate various equilibrium problems arising in economics and engineerings. Recently, for solving complementarity problems, various equivalent equation formulations have been proposed and seem attractive. However, such formulations have the difficulty that the equation arising from complementarity problems is typically nonsmooth. In this paper, we propose a new smoothing Newton method for nonsmooth equations. In our method, we use an approximation function that is smooth when the approximation parameter is positive, and which coincides with original nonsmooth function when the parameter takes zero. Then, we apply Newton's method for the equation that is equivalent to the original nonsmooth equation and that includes an approximation parameter as a variable. The proposed method has the advantage that it has only to deal with a smooth function at any iteration and that it never requires a procedure to decrease an approximation parameter. We show that the sequence generated by the proposed method is globally convergent to a solution, and that, under semismooth assumption, its convergence rate is superlinear. Moreover, we apply the method to nonlinear complementarity problems. Numerical results show that the proposed method is practically efficient.

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Authors and Affiliations

  1. Department of Systems and Human Science, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka, 560-8531, Japan

    Kouichi Taji

  2. 1st Personal C & C Operations Unit, NEC Corporation, 1-10 Nisshincho, Fuchu, Tokyo, 183-8501, Japan

    Motohiro Miyamoto

Authors
  1. Kouichi Taji
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  2. Motohiro Miyamoto
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Taji, K., Miyamoto, M. A Globally Convergent Smoothing Newton Method for Nonsmooth Equations and Its Application to Complementarity Problems. Computational Optimization and Applications 22, 81–101 (2002). https://doi.org/10.1023/A:1014886302772

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