A Regularization Semismooth Newton Method for $P_0$-NCPs with a Non-Monotone Line Search

A Regularization Semismooth Newton Method for $P_0$-NCPs with a Non-Monotone Line Search

Year:    2012

Numerical Mathematics: Theory, Methods and Applications, Vol. 5 (2012), Iss. 2 : pp. 186–204

Abstract

In this paper, we propose a regularized version of the generalized NCP-function proposed by Hu, Huang and Chen [J. Comput. Appl. Math., 230 (2009), pp. 69-82]. Based on this regularized function, we propose a semismooth Newton method for solving nonlinear complementarity problems, where a non-monotone line search scheme is used. In particular, we show that the proposed non-monotone method is globally and locally superlinearly convergent under suitable assumptions. We test the proposed method by solving the test problems from MCPLIB. Numerical experiments indicate that this algorithm has better numerical performance in the case of $p=5$ and $\theta\in[0.25,075]$  than other cases.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/nmtma.2012.m10027

Numerical Mathematics: Theory, Methods and Applications, Vol. 5 (2012), Iss. 2 : pp. 186–204

Published online:    2012-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    19

Keywords:    Nonlinear complementarity problem non-monotone line search semismooth Newton method global convergence local superlinear convergence.