|edoc-Server der Humboldt-Universität zu Berlin|
Teemu Pennanen, Helsinki School of Economics|
Matti Koivu, Helsinki School of Economics
|Title:||Integration quadratures in discretization of stochastic programs|
|Date of Acceptance:||04.06.2002|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.||Endnote Bibtex|
|print on demand: If you click on this icon you can order a print copy of this publication.|
|Because of its simplicity, conditional sampling is the most popular method for generating scenario trees in stochastic programming. It is based on approximating probability measures by empirical ones generated by random samples. Because of computational restrictions, these samples cannot be very large, so the empirical measures can be poor approximations of the original ones. This paper shows that modern integration quadratures provide a simple and an attractive alternative to random sampling. These quadratures are designed to give good approximations of given (probability) measures by a small number of quadrature points. The performance of the resulting scenario generation methods is demonstrated by numerical examples.|
These data concerning access statistics for individual documents
have been compiled using the webserver log files aggregated by AWSTATS.
They refer to a monthly access count to the full text documents as well as to the entry page.
As for format versions of a document which consist of multiple files (such as HTML) the highest monthly access number to one of the files (chapters) is shown respectivly.
To see the detailled access numbers please move the mouse pointer over the single bars of the digaram.
Gesamtzahl der Zugriffe seit Jul 2011: