A nonmonotone smoothing Newton algorithm for solving nonlinear complementarity problems

The smoothing-type algorithm has been a powerful tool for solving various optimization problems. In order to improve the numerical results of the algorithm, the nonmonotone line search technique has been used when the algorithm is implemented. However, the theoretical analysis is based on the algori...

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Veröffentlicht in:	Optimization methods & software Jg. 24; H. 3; S. 447 - 460
Hauptverfasser:	Hu, Sheng-Long, Huang, Zheng-Hai, Wang, Ping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Taylor & Francis 01.06.2009
Schlagworte:	global convergence line search local superlinear convergence nonlinear complementarity problem smoothing-type algorithm
ISSN:	1055-6788, 1029-4937
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	The smoothing-type algorithm has been a powerful tool for solving various optimization problems. In order to improve the numerical results of the algorithm, the nonmonotone line search technique has been used when the algorithm is implemented. However, the theoretical analysis is based on the algorithm with some monotone line search. In this paper, based on the smoothed Kanzow-Kleinmichel NCP function, we propose a smoothing Newton algorithm for solving the nonlinear complementarity problem with a new nonmonotone line search. We show that the nonmonotone algorithm is globally and locally superlinearly convergent under suitable assumptions. The preliminary numerical results are also reported.
ISSN:	1055-6788 1029-4937
DOI:	10.1080/10556780902769862