Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
