Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/5415

TitleA primal-dual interior-point algorithm for nonlinear least squares constrained problems
Author(s)Costa, M. Fernanda P.
Fernandes, Edite Manuela da G. P.
KeywordsLeast squares
Factorized quasi-newton methods
Primal-dual interior-point method
Issue date2005
PublisherSociedad Española de Estadística e Investigación Operativa
Citation"Sociedad de estadística e investigación operativa". 13:1 (2005) 145-166.
Abstract(s)This paper extends prior work by the authors on solving nonlinear least squares unconstrained problems using a factorized quasi-Newton technique. With this aim we use a primal-dual interior-point algorithm for nonconvex nonlinear program- ming. The factorized quasi-Newton technique is now applied to the Hessian of the Lagrangian function for the transformed problem which is based on a logarithmic barrier formulation. We emphasize the importance of establishing and maintain- ing symmetric quasi-definiteness of the reduced KKT system. The algorithm then tries to choose a step size that reduces a merit function, and to select a penalty parameter that ensures descent directions along the iterative process. Computa- tional results are included for a variety of least squares constrained problems and preliminary numerical testing indicates that the algorithm is robust and efficient in practice.
TypeArticle
URIhttp://hdl.handle.net/1822/5415
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals
LES/ALG - Artigos em revistas científicas internacionais com arbitragem

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