Augmented Lagrangian methods under the constant positive linear dependence constraint qualification
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
20/10/2012
20/10/2012
2008
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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 |
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 |