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New algorithms based on the interior point method for convex quadratic programming
(Maltepe Üniversitesi, 2009) Tahmasebzadeh, S.; Navidi, H.; Malek, A.
This paper presents three new algorithms for solving convex quadratic programming problems subject to the linear constraints. These algorithms are based on the general theory of Karmarkar interior points techniques. The first one uses the Karmarkar idea and linearization of the objective function. The second and third algorithms are modification of the first algorithm using the Schrijver and Malek-Naseri approaches respectively. These three new schemes are tested against the algorithm of Kebbiche-Keraghel-Yassine (KKY). It is shown that these three new algorithms are more efficient and converge to the correct optimal solution, while the KKY algorithm does not converge in some cases. Numerical results are given to illustrate the performance of the new algorithms.