Scenarios for Multistage Stochastic Programs
Jitka Dupačová (),
Giorgio Consigli () and
Stein Wallace
Annals of Operations Research, 2000, vol. 100, issue 1, 25-53
Abstract:
A major issue in any application of multistage stochastic programming is the representation of the underlying random data process. We discuss the case when enough data paths can be generated according to an accepted parametric or nonparametric stochastic model. No assumptions on convexity with respect to the random parameters are required. We emphasize the notion of representative scenarios (or a representative scenario tree) relative to the problem being modeled. Copyright Kluwer Academic Publishers 2000
Keywords: scenarios and scenario trees; clustering; importance sampling; matching moments; problem oriented requirements; inference and bounds (search for similar items in EconPapers)
Date: 2000
References: Add references at CitEc
Citations: View citations in EconPapers (88)
Downloads: (external link)
http://hdl.handle.net/10.1023/A:1019206915174 (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:100:y:2000:i:1:p:25-53:10.1023/a:1019206915174
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1023/A:1019206915174
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 ().