-

 

 

 




Optimization Online





 

Global minimization using an Augmented Lagrangian method with variable lower-level constraints

Ernesto G. Birgin(egbirgin***at***ime.usp.br)
Christodoulos A. Floudas(floudas***at***titan.princeton.edu)
José Mario Martínez(martinez***at***ime.unicamp.br)

Abstract: A novel global optimization method based on an Augmented Lagrangian framework is introduced for continuous constrained nonlinear optimization problems. At each outer iteration the method requires the $\varepsilon$-global minimization of the Augmented Lagrangian with simple constraints. Global convergence to an $\varepsilon$-global minimizer of the original problem is proved. The subproblems are solved using the $\alpha$BB method. Numerical experiments are presented.

Keywords: Deterministic global optimization, Augmented Lagrangians, nonlinear programming, algorithms, numerical experiments.

Category 1: Global Optimization

Citation:

Download: [PDF]

Entry Submitted: 12/12/2006
Entry Accepted: 12/12/2006
Entry Last Modified: 12/12/2006

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