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Type: Artigo de periódico
Title: Improving ultimate convergence of an augmented Lagrangian method
Author: BIRGIN, E. G.
Abstract: Optimization methods that employ the classical Powell-Hestenes-Rockafellar augmented Lagrangian are useful tools for solving nonlinear programming problems. Their reputation decreased in the last 10 years due to the comparative success of interior-point Newtonian algorithms, which are asymptotically faster. In this research, a combination of both approaches is evaluated. The idea is to produce a competitive method, being more robust and efficient than its `pure` counterparts for critical problems. Moreover, an additional hybrid algorithm is defined, in which the interior-point method is replaced by the Newtonian resolution of a Karush-Kuhn-Tucker (KKT) system identified by the augmented Lagrangian algorithm. The software used in this work is freely available through the Tango Project web page: to egbirgin/tango/.
Subject: nonlinear programming
augmented Lagrangian methods
interior-point methods
Newton`s method
Country: Inglaterra
Citation: OPTIMIZATION METHODS & SOFTWARE, v.23, n.2, p.177-195, 2008
Rights: fechado
Identifier DOI: 10.1080/10556780701577730
Date Issue: 2008
Appears in Collections:IMECC - Artigos e Outros Documentos

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