Separable Programming

Theory and Methods

S.M. Stefanov (Autor)

Buch | Softcover

314 Seiten

2010 | Softcover reprint of hardcover 1st ed. 2001
Springer-Verlag New York Inc.
978-1-4419-4851-9 (ISBN)

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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.

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.

Erscheint lt. Verlag	6.12.2010
Reihe/Serie	Applied Optimization ; 53
Zusatzinfo	XIX, 314 p.
Verlagsort	New York, NY
Sprache	englisch
Maße	155 x 235 mm
Gewicht	522 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik
	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
ISBN-10	1-4419-4851-1 / 1441948511
ISBN-13	978-1-4419-4851-9 / 9781441948519
Zustand	Neuware