Stefan M. Stefanov
Separable Programming - Applied Optimization Stefan M. Stefanov 1st Ed. Softcover of Orig. Ed. 2001 edition

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Separable Programming - Applied Optimization

Stefan M. Stefanov

1st Ed. Softcover of Orig. Ed. 2001 edition

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.

314 pages, biography

Médias	Livres Paperback Book (Livre avec couverture souple et dos collé)
Validé	6 décembre 2010
ISBN13	9781441948519
Éditeurs	Springer-Verlag New York Inc.
Pages	314
Dimensions	156 × 234 × 18 mm · 476 g
Langue et grammaire	Anglais