Some advances in decomposition methodsfor stochastic linear programming

Andrzej Ruszczynski ()

Annals of Operations Research, 1999, vol. 85, issue 0, 153-172

Abstract: Stochastic programming problems have very large dimension and characteristic structureswhich are tractable by decomposition. We review some new developments in cutting planemethods, augmented Lagrangian and splitting methods for linear multi‐stage stochasticprogramming problems. Copyright Kluwer Academic Publishers 1999

Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1018965626303 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:85:y:1999:i:0:p:153-172:10.1023/a:1018965626303

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/A:1018965626303

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().