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Titre: THEORETICAL AND NUMERICAL RESULT FOR LINEAR SEMIDEFINITE PROGRAMMING BASED ON A NEW KERNEL FUNCTION
Auteur(s): ABDERRAHIM, GUEMMAZ
Mots-clés: linear semidefinite programming; central trajectory methods;
primal-dual interior point methods
Date de publication: 2022
Editeur: J. Math. Comput. Sci.
Résumé: Kernel functions serve the central goal of creating new search directions for the primal-dual interiorpoint algorithm to solve linear optimization problems. A significantly improved primal-dual interior-point algorithm for linear optimization is presented based on a novel kernel function. We show a primal-dual interior-point technique for linear optimization based on a class of kernel functions that are eligible. This research presents a new efficient kernel function-based primal-dual IPM algorithm for semidefinite programming problems based on the Nesterov-Todd (NT) direction. With a new and simple technique, we propose a new kernel function to obtain an optimal solution of the perturbed problem (SDP)m.
URI/URL: http://dspace.cu-barika.dz/jspui/handle/123456789/513
Collection(s) :Department of Maths - قسم الرياضيات

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