Augmented Lagrangian methods under the Constant Positive Linear Dependence constraint qualification
Roberto Andreani (andreaniime.unicamp.br)
Abstract: Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.
Keywords: Nonlinear programming, Augmented Lagrangian methods, KKT systems, numerical experiments.
Category 1: Nonlinear Optimization
Citation: Technical Report 36/04. IMECC-UNICAMP, University of Campinas, CP 6065, 13081-970 Campinas SP, Brazil. 08/2004
Entry Submitted: 09/10/2004
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