New techniques for determining search directions of interior point algorithms in optimization / Billel Zaoui  

Public ISBD Titre : New techniques for determining search directions of interior point algorithms in optimization Type de document : document électronique Auteurs : Billel Zaoui, Auteur ; Djamel Benterki, Directeur de thèse ; Samia KIhelladi Editeur : Setif:UFA Année de publication : 2024 Importance : 1 vol (146 f.) Format : 29 cm Langues : Français (fre) Catégories : Thèses & Mémoires:Mathématique Mots-clés : Linear programming, Convex quadratic programming, Semidefinite programming, Primal dual interior point method, Algebraic transformation, Descent direction Index. décimale : 510 - Mathématique Résumé : This thesis deals with solving optimization problems using primal dual interior point methods. By employing algebraic transformations of centrality equations, we conducted a theoretical and algorithmic study on four optimization problems: linear programming, convex quadratic programming, l inear semi definite programming and convex quadratic semi definite programming. For each problem, through various algebraic transformations, we demonstrated the convergence of the proposed algorithms and provided the rates of their polynomial algorithmic complexities. The obtained results are reinforced by hi ghly significant numerical experiments. Côte titre : DM/0201 En ligne : http://dspace.univ-setif.dz:8888/jspui/handle/123456789/4408 Format de la ressource électronique : pdf New techniques for determining search directions of interior point algorithms in optimization [document électronique] / Billel Zaoui, Auteur ; Djamel Benterki, Directeur de thèse ; Samia KIhelladi . - [S.l.] : Setif:UFA, 2024 . - 1 vol (146 f.) ; 29 cm. Langues : Français (fre) Catégories : Thèses & Mémoires:Mathématique Mots-clés : Linear programming, Convex quadratic programming, Semidefinite programming, Primal dual interior point method, Algebraic transformation, Descent direction Index. décimale : 510 - Mathématique Résumé : This thesis deals with solving optimization problems using primal dual interior point methods. By employing algebraic transformations of centrality equations, we conducted a theoretical and algorithmic study on four optimization problems: linear programming, convex quadratic programming, l inear semi definite programming and convex quadratic semi definite programming. For each problem, through various algebraic transformations, we demonstrated the convergence of the proposed algorithms and provided the rates of their polynomial algorithmic complexities. The obtained results are reinforced by hi ghly significant numerical experiments. Côte titre : DM/0201 En ligne : http://dspace.univ-setif.dz:8888/jspui/handle/123456789/4408 Format de la ressource électronique : pdf

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
DM/0201	DM/0201	Thèse	Bibliothéque des sciences	Anglais	Disponible Disponible

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