Augmented Lagrangian methods under the constant positive linear dependence constraint qualification


Autoria(s): ANDREANI, R.; BIRGIN, E. G.; MARTINEZ, J. M.; SCHUVERDT, M. L.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2008

Resumo

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.

Identificador

MATHEMATICAL PROGRAMMING, v.111, n.1/Fev, p.5-32, 2008

0025-5610

http://producao.usp.br/handle/BDPI/30419

10.1007/s10107-006-0077-1

http://dx.doi.org/10.1007/s10107-006-0077-1

Idioma(s)

eng

Publicador

SPRINGER

Relação

Mathematical Programming

Direitos

restrictedAccess

Copyright SPRINGER

Palavras-Chave #nonlinear programming #augmented Lagrangian methods #KKT systems #numerical experiments #PROJECTED GRADIENT METHODS #VARIATIONAL-INEQUALITIES #SIMPLE BOUNDS #CONVEX-SETS #OPTIMIZATION #EQUALITY #ALGORITHMS #REFORMULATION #CONVERGENCE #OPTIMALITY #Computer Science, Software Engineering #Operations Research & Management Science #Mathematics, Applied
Tipo

article

proceedings paper

publishedVersion