Stochastic Decomposition

Stochastic Decomposition
Author: Julia L. Higle
Publisher: Springer Science & Business Media
Total Pages: 237
Release: 2013-11-27
Genre: Mathematics
ISBN: 1461541158

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Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP optimization models. There are several arenas model is appropriate, and such models have found applications in air line yield management, capacity planning, electric power generation planning, financial planning, logistics, telecommunications network planning, and many more. In some of these applications, modelers represent uncertainty in terms of only a few seenarios and formulate a large scale linear program which is then solved using LP software. However, there are many applications, such as the telecommunications planning problem discussed in this book, where a handful of seenarios do not capture variability well enough to provide a reasonable model of the actual decision-making problem. Problems of this type easily exceed the capabilities of LP software by several orders of magnitude. Their solution requires the use of algorithmic methods that exploit the structure of the SLP model in a manner that will accommodate large scale applications.


Stochastic Decomposition
Language: en
Pages: 237
Authors: Julia L. Higle
Categories: Mathematics
Type: BOOK - Published: 2013-11-27 - Publisher: Springer Science & Business Media

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Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP
Stochastic Decomposition
Language: en
Pages: 254
Authors: Julia L. Higle
Categories: Business & Economics
Type: BOOK - Published: 1996-02-29 - Publisher: Springer Science & Business Media

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This book summarizes developments related to a class of methods called Stochastic Decomposition (SD) algorithms, which represent an important shift in the desig
Upper and Lower Bounds for Stochastic Processes
Language: en
Pages: 727
Authors: Michel Talagrand
Categories: Mathematics
Type: BOOK - Published: 2022-01-01 - Publisher: Springer Nature

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This book provides an in-depth account of modern methods used to bound the supremum of stochastic processes. Starting from first principles, it takes the reader
Two-stage Stochastic Linear Programming: Stochastic Decomposition Approaches (PHD).
Language: en
Pages: 0
Authors: Diana Schadl Yakowitz
Categories:
Type: BOOK - Published: 1991 - Publisher:

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Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming
Language: en
Pages: 178
Authors: Christian Küchler
Categories: Mathematics
Type: BOOK - Published: 2010-05-30 - Publisher: Springer Science & Business Media

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Christian Küchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic