Primal-dual Interior Point Method For Linear Programming Based On a New Wide Neighborhood / Zineb Lalouni

Public ISBD Titre : Primal-dual Interior Point Method For Linear Programming Based On a New Wide Neighborhood Type de document : document électronique Auteurs : Zineb Lalouni, Auteur ; Assala Nasri, Auteur ; Kettab.Samia, Directeur de thèse Editeur : Sétif:UFS Année de publication : 2026 Importance : 1 vol (59 f.) Format : 29 cm Note générale : Langues : Anglais (eng) Catégories : Mathématique Mots-clés : Linear programming, Interior point methods, Large-step algorithm· Wide neighbourhood· Polynomial complexity Résumé : This work is devoted to the theoretical and numerical study of interior-point meth- ods, and more specifically, central-path primal-dual algorithms for linear program- ming. Recognized for their polynomial complexity, convergence rate, and numerical efficiency, these approaches are enhanced here by the introduction of a new large neighborhood developed by Darvay in 2018. The proposed algorithm is polynomial in time and achieves the best complexity bound known to date for interior-point methods applied to linear programming. Finally, this dissertation concludes with a numerical study that demonstrates the practical effectiveness of the proposed approach. Côte titre : MAM/0856 Primal-dual Interior Point Method For Linear Programming Based On a New Wide Neighborhood [document électronique] / Zineb Lalouni, Auteur ; Assala Nasri, Auteur ; Kettab.Samia, Directeur de thèse . - [S.l.] : Sétif:UFS, 2026 . - 1 vol (59 f.) ; 29 cm. Langues : Anglais (eng) Catégories : Mathématique Mots-clés : Linear programming, Interior point methods, Large-step algorithm· Wide neighbourhood· Polynomial complexity Résumé : This work is devoted to the theoretical and numerical study of interior-point meth- ods, and more specifically, central-path primal-dual algorithms for linear program- ming. Recognized for their polynomial complexity, convergence rate, and numerical efficiency, these approaches are enhanced here by the introduction of a new large neighborhood developed by Darvay in 2018. The proposed algorithm is polynomial in time and achieves the best complexity bound known to date for interior-point methods applied to linear programming. Finally, this dissertation concludes with a numerical study that demonstrates the practical effectiveness of the proposed approach. Côte titre : MAM/0856

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