Publicação

On interior point multidimensional filter line search methods for constrained optimization

Detalhes bibliográficos
Resumo:	This paper aims to compare primal-dual interior point multidimensional filter line search methods for nonlinear programming. The multidimensional filter is based on the constraint violations and aims to enforce their convergence to zero. To prevent convergence to feasible nonoptimal points a standard monotone sufficient reduction condition is also imposed on the barrier function for a trial iterate to be acceptable. Nonmonotone reduction conditions that allow an increase in the filter entries and in the barrier function at each iteration are also implemented. Numerical experiments with both variants as well as a comparison with a merit function approach are reported.
Autores principais:	Costa, M. Fernanda P.
Outros Autores:	Fernandes, Edite Manuela da G. P.
Assunto:	Filter line search method Interior point method Nonlinear optimization
Ano:	2007
País:	Portugal
Tipo de documento:	artigo
Tipo de acesso:	acesso aberto
Instituição associada:	Universidade do Minho
Idioma:	inglês
Origem:	RepositóriUM - Universidade do Minho

Descrição
Resumo:	This paper aims to compare primal-dual interior point multidimensional filter line search methods for nonlinear programming. The multidimensional filter is based on the constraint violations and aims to enforce their convergence to zero. To prevent convergence to feasible nonoptimal points a standard monotone sufficient reduction condition is also imposed on the barrier function for a trial iterate to be acceptable. Nonmonotone reduction conditions that allow an increase in the filter entries and in the barrier function at each iteration are also implemented. Numerical experiments with both variants as well as a comparison with a merit function approach are reported.