-

 

 

 




Optimization Online





 

Augmented Lagrangian methods under the Constant Positive Linear Dependence constraint qualification

Roberto Andreani (andreani***at***ime.unicamp.br)
Ernesto Birgin (egbirgin***at***ime.usp.br)
José Mario Martínez (martinez***at***ime.unicamp.br)
María Laura Schuverdt (schuverd***at***ime.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

Download: [Postscript][PDF]

Entry Submitted: 09/10/2004
Entry Accepted: 09/10/2004
Entry Last Modified: 09/13/2004

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society