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Separable Optimization

Theory and Methods

Produktform: Buch / Einband - flex.(Paperback)

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 I and I norms, as a convex separable nonsmooth unconstrained minimization problem, is considered as well. Advanced undergraduate and graduate students, mathematical programming/ operations research specialists.weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Sprache(n): Englisch

ISBN: 978-3-030-78403-4 / 978-3030784034 / 9783030784034

Verlag: Springer International Publishing

Erscheinungsdatum: 27.11.2022

Seiten: 356

Auflage: 2

Autor(en): Stefan M. Stefanov

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