Hochreiter, Ronald
Scenario Optimization for Multi-Stage Stochastic Programming Problems
Abstract
The field of multi-stage stochastic programming provides a rich modelling framework to tackle a broad range of real-world decision problems. In order to numerically solve such programs - once they get reasonably large - the infinite-dimensional optimization problem has to be discretized. The stochastic optimization program generally consists of an optimization model and a stochastic model. In the multi-stage case the stochastic model is most commonly represented as a multi-variate stochastic process. The most common technique to calculate an useable discretization is to generate a scenario tree from the underlying stochastic process. In the first part of the talk we take a look at scenario optimization from the viewpoint of a decision taker, to provide rather non-technical insights into the problem. In the second part of the talk we examplify scenario tree generation by reviewing one specific algorithm based on multi-dimensional facility location applying backward stagewise clustering. An example from the area of financial engineering concludes the talk.
BibTeX - Entry
@InProceedings{hochreiter:DSP:2005:61,
author = {Ronald Hochreiter},
title = {Scenario Optimization for Multi-Stage Stochastic Programming Problems},
booktitle = {Algorithms for Optimization with Incomplete Information},
year = {2005},
editor = {Susanne Albers and Rolf H. M{\"o}hring and Georg Ch. Pflug and R{\"u}diger Schultz},
number = {05031},
series = {Dagstuhl Seminar Proceedings},
ISSN = {1862-4405},
publisher = {Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2005/61},
annote = {Keywords: Stochastic programming, scenario generation, facility location, financial engineering}
}
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Keywords: |
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Stochastic programming, scenario generation, facility location, financial engineering |
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Seminar: |
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05031 - Algorithms for Optimization with Incomplete Information
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Issue date: |
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2005 |
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Date of publication: |
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30.05.2005 |
30.05.2005
