On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs
A general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two different ways: by decomposing the problem into scenarios or decomposing it into nodes corresponding to stages. In both cases the method has favorable convergence properties and a structure which makes it convenient for parallel computing environments.
|Date of creation:||Feb 1994|
|Date of revision:|
|Contact details of provider:|| Postal: A-2361 Laxenburg|
Web page: http://www.iiasa.ac.at/Publications/Catalog/PUB_ONLINE.html
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- A. Ruszczynski, 1992. "Augmented Lagrangian Decomposition for Sparse Convex Optimization," Working Papers wp92075, International Institute for Applied Systems Analysis.
- Alan S. Manne & Richard G. Richels, 1991. "Global CO2 Emission Reductions - the Impacts of Rising Energy Costs," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 87-108.
- Alan Manne & Richard Richels, 1992. "Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits," MIT Press Books, The MIT Press, edition 1, volume 1, number 026213280x, March.
When requesting a correction, please mention this item's handle: RePEc:wop:iasawp:wp94005. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel)
If references are entirely missing, you can add them using this form.