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Linear programming with MATLAB / Michael C. FERRIS (Cop. 2007)
Titre : Linear programming with MATLAB Type de document : texte imprimé Auteurs : Michael C. FERRIS, Auteur ; Olvi L. MANGASARIAN, Auteur ; Stephen J. WRIGHT, Auteur Editeur : Philadelphie [U.S.A] : Society for Industrial and Applied Mathematics Année de publication : Cop. 2007 Autre Editeur : Philadelphie [U.S.A] : Mathematical Programming Society Collection : MOS-SIAM Series on Optimization Importance : X-266 p. ISBN/ISSN/EAN : 978-0-89871-643-6 Langues : Anglais Mots-clés : programmation linéaire optimisation MATLAB convexité algèbre linéaire Résumé : This textbook provides a self-contained introduction to linear programming using MATLAB® software to elucidate the development of algorithms and theory. Early chapters cover linear algebra basics, the simplex method, duality, the solving of large linear problems, sensitivity analysis, and parametric linear programming. In later chapters, the authors discuss quadratic programming, linear complementarity, interior-point methods, and selected applications of linear programming to approximation and classification problems. Note de contenu : index, bibliogr Linear programming with MATLAB [texte imprimé] / Michael C. FERRIS, Auteur ; Olvi L. MANGASARIAN, Auteur ; Stephen J. WRIGHT, Auteur . - Philadelphie (U.S.A) : Society for Industrial and Applied Mathematics : Philadelphie (U.S.A) : Mathematical Programming Society, Cop. 2007 . - X-266 p.. - (MOS-SIAM Series on Optimization) .
ISBN : 978-0-89871-643-6
Langues : Anglais
Mots-clés : programmation linéaire optimisation MATLAB convexité algèbre linéaire Résumé : This textbook provides a self-contained introduction to linear programming using MATLAB® software to elucidate the development of algorithms and theory. Early chapters cover linear algebra basics, the simplex method, duality, the solving of large linear problems, sensitivity analysis, and parametric linear programming. In later chapters, the authors discuss quadratic programming, linear complementarity, interior-point methods, and selected applications of linear programming to approximation and classification problems. Note de contenu : index, bibliogr Exemplaires
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