M?todos de punto interior para optimizaci?n cuadr?tica convexa con matrices no definidas positivas

In this article a modification of the recursive algorithm of Cholesky is obtainedthat allows the factorization of Semi Definite Positive Matrices, even though theseare not positive defined, without increasing the computational cost. Thanks to thisfactorization Convex Quadratic Programming Problems a...

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Main Authors: Palencia F., Gonzalo, Hing C., Rosina, Rojas C., Mariledy, Medina S., Denysde
Format: Artículo
Language: Español
Published: 2015
Online Access: http://revistas.ucr.ac.cr/index.php/matematica/article/view/284
http://hdl.handle.net/10669/12934
Summary: In this article a modification of the recursive algorithm of Cholesky is obtainedthat allows the factorization of Semi Definite Positive Matrices, even though theseare not positive defined, without increasing the computational cost. Thanks to thisfactorization Convex Quadratic Programming Problems are transformed into SecondOrder Conical Problems, which are solved with the aid of the generalization of thePredictor-Corrector algorithm of Mehrotra for these problems. There are carried outnumeric experiments for validating the results.Keywords: convex quadratic programming, second-order cones, interior point methods.