Separable Programming: Theory and Methods - S. M. Stefanov
- Format: Broché Voir le descriptif
Vous en avez un à vendre ?
Vendez-le-vôtre277,99 €
Occasion · Comme Neuf
Ou 69,50 € /mois
- Livraison : 25,00 €
- Livré entre le 17 et le 27 avril
- Payez directement sur Rakuten (CB, PayPal, 4xCB...)
- Récupérez le produit directement chez le vendeur
- Rakuten vous rembourse en cas de problème
Gratuit et sans engagement
Félicitations !
Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !
TROUVER UN MAGASIN
Retour
Avis sur Separable Programming: Theory And Methods de S. M. Stefanov Format Broché - Livres
0 avis sur Separable Programming: Theory And Methods de S. M. Stefanov Format Broché - Livres
Donnez votre avis et cumulez 5
Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.
Présentation Separable Programming: Theory And Methods de S. M. Stefanov Format Broché
- Livres
Résumé :
In this book, the author considers separable programming and, in particular, one of its important cases - convex separable programming. Some general results are presented, techniques of approximating the separable problem by linear programming and dynamic programming are considered. Convex separable programs subject to inequality/ equality constraint(s) and bounds on variables are also studied and iterative algorithms of polynomial complexity are proposed. As an application, these algorithms are used in the implementation of stochastic quasigradient methods to some separable stochastic programs. Numerical approximation with respect to I1 and I4 norms, as a convex separable nonsmooth unconstrained minimization problem, is considered as well. Audience: Advanced undergraduate and graduate students, mathematical programming/ operations research specialists.
Sommaire:
List of Figures. List of Tables. Preface. 1. Preliminaries: Convex Analysis and Convex Programming. Part One: Separable Programming. 2. Introduction. Approximating the Separable Problem. 3. Convex Separable Programming. 4. Separable Programming: A Dynamic Programming Approach. Part Two: Convex Separable Programming with Bounds on the Variables. 5. Statement of the Main Problem. Basic Result. 6. Version One: Linear Equality Constraints. 7. The Algorithms. 8. Version Two: Linear Constraint of the Form `>='. 9. Well-Posedness of Optimization Problems. On the Stability of the Set of Saddle Points of the Lagrangian. 10. Extensions. 11. Applications and Computational Experiments. Part Three: Selected Supplementary Topics and Applications. 12. Approximations with Respect to l1- and lINFINITY-Norms: An Application of Convex Separable Unconstrained Nondifferentiable Optimization. 13. About Projections in the Implementation of Stochastic Quasigradient Methods to Some Probabilistic Inventory Control Problems. The Stochastic Problem of Best Chebyshev Approximation. 14. Integrality of the Knapsack Polytope. Appendices. Bibliography. Index. Notation. List of Statements.
Détails de conformité du produit
Personne responsable dans l'UE