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A smoothing conic trust region filter method for the nonlinear complementarity problem

✍ Scribed by Ying Zhou

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
771 KB
Volume
229
Category
Article
ISSN
0377-0427

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✦ Synopsis

This paper discusses nonlinear complementarity problems; its goal is to present a globally and superlinearly convergent algorithm for the discussed problems. Filter methods are extensively studied to handle nonlinear complementarity problem. Because of good numerical results, filter techniques are attached. By means of a filter strategy, we present a new trust region method based on a conic model for nonlinear complementarity problems. Under a proper condition, the superlinear convergence of the algorithm is established without the strict complementarity condition.

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