A smoothing conic trust region filter method for the nonlinear complementarity problem
type: Item
instance of: scholarly article
title: A smoothing conic trust region filter method for the nonlinear complementarity problem
zbMATH Open document ID: 1167.65037
author: Ying Zhou
published in: Journal of Computational and Applied Mathematics
publication date: 2009-06-11T00:00:00Z
review text: In this paper, a new conic trust region filter method is proposed to solve the nonlinear complementarity problem by combining the advantage of a trust region based on the conic model and filter method. The author shows that every accumulation point of the sequence generated by the algorithm is a solution of the nonlinear complementarity problem. The global convergence is proved. Under a nonsingularity condition, the superlinear convergence of the algorithm is established in the absence of strict complementarity.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C33
Mathematics Subject Classification ID: 90C51
zbMATH DE Number: 5564263
zbMATH Keywords: nonlinear complementarity problem
zbMATH Keywords: trust region method
zbMATH Keywords: conic model
zbMATH Keywords: filter method
zbMATH Keywords: global convergence
zbMATH Keywords: algorithm
zbMATH Keywords: superlinear convergence
MaRDI profile type: Publication
full work available at URL: j.cam.2008.10.057
OpenAlex ID: W2159162654
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DOI: 10.1016/J.CAM.2008.10.057
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description: scientific article; zbMATH DE number 5564263