Multistage Stochastic Integer Programs : An Introduction

We consider linear multistage stochastic integer programs and study their functional and dynamic programming formulations as well as conditions for optimality and stability of solutions. Furthermore, we study the application of the Rockafellar-Wets dualization approach as well as the structure and algorithmic potential of corresponding dual problems. For discrete underlying probability distributions we discuss possible large scale mixed-integer linear programming formulations and three dual decomposition approaches, namely, scenario, component and nodal decomposition.

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Date Created:
10.06.2001
Date Issued:
26.06.2012
URN:
urn:nbn:de:hbz:464-20120626-144118-1
PURL:
http://purl.oclc.org/NET/duett-05272002-074041
DOI:
10.1007/978-3-662-04331-8_29
Language:
English
Type of Resource:
Text
Keywords:
90C15 Stochastic programming; 49M27 Decomposition methods
Collection:
E-Publications
Dewey Decimal Classification:
510 Mathematics
Subject categories of the Deutsche Nationalbibliografie:
510 Mathematics
Hosting institution:
Faculty of Mathematics
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This is a post-peer-review, pre-copyedit version of this article:

Römisch W., Schultz R.: Multistage Stochastic Integer Programs: An Introduction. In: Grötschel M., Krumke S.O., Rambau J. (eds) Online Optimization of Large Scale Systems. - Berlin, Heidelberg: Springer, 2001

The final authenticated version is available online at: https://doi.org/10.1007/978-3-662-04331-8_29

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