edoc-Server der Humboldt-Universität zu Berlin

SPEPS Preprint

Author(s): Holger Heitsch, Humboldt-University
Hernan Leövey, Humboldt-University
Werner Römisch, Humboldt-University
Title: Are Quasi-Monte Carlo algorithms efficient for two-stage stochastic programs?
Date of Acceptance: 24.09.2012
Submission Date: 01.06.2012
Series Title: Stochastic Programming E-Print Series
(SPEPS)
Editors: Julie L. Higle; Werner Römisch; Surrajeet Sen
Complete Preprint: pdf (urn:nbn:de:kobv:11-100204148)
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. Bestellung als gedruckte und gebundene Version bei epubli.de, Ausführung der Bestellung erst nach Bestätigung auf den epubli.de-Seiten
Diese Seite taggen: These icons lead to social bookmarking systems where you can create and manage personal bookmarks and discover bookmakrs of other users.
  • connotea
  • del.icio.us
  • Furl
  • RawSugar

Abstract (eng):
Quasi-Monte Carlo algorithms are studied for designing discrete approximations of two-stage linear stochastic programs. Their integrands are piecewise linear, but neither smooth nor lie in the function spaces considered for QMC error analysis. We show that under some weak geometric condition on the two-stage model all terms of their ANOVA decomposition, except the one of highest order, are smooth. Hence, Quasi-Monte Carlo algorithms may achieve the optimal rate of convergence $O(n^{-1+\delta}$ with $\delta \in (0,\frac{1}{2}]$ and a constant not depending on the dimension. The geometric condition is shown to be generically satis fied if the underlying distribution is normal. We discuss sensitivity indices, e ffective dimensions and dimension reduction techniques for two-stage integrands. Numerical experiments show that indeed convergence rates close to the optimal rate are achieved when using randomly scrambled Sobol' point sets and randomly shifted lattice rules accompanied with suitable dimension reduction techniques.
Access Statistics: 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.
Startseite: 11 Zugriffe PDF: 2 Zugriffe PDF: 7 Zugriffe PDF: 9 Zugriffe Startseite: 7 Zugriffe PDF: 6 Zugriffe Startseite: 3 Zugriffe PDF: 7 Zugriffe Startseite: 6 Zugriffe PDF: 5 Zugriffe Startseite: 8 Zugriffe PDF: 12 Zugriffe Startseite: 3 Zugriffe PDF: 5 Zugriffe Startseite: 2 Zugriffe PDF: 4 Zugriffe Startseite: 4 Zugriffe PDF: 6 Zugriffe Startseite: 1 Zugriffe PDF: 3 Zugriffe PDF: 4 Zugriffe Startseite: 3 Zugriffe PDF: 1 Zugriffe Startseite: 3 Zugriffe PDF: 4 Zugriffe Startseite: 1 Zugriffe PDF: 1 Zugriffe Startseite: 1 Zugriffe PDF: 2 Zugriffe Startseite: 1 Zugriffe PDF: 5 Zugriffe Startseite: 1 Zugriffe PDF: 7 Zugriffe Startseite: 1 Zugriffe PDF: 9 Zugriffe Startseite: 6 Zugriffe PDF: 8 Zugriffe PDF: 9 Zugriffe Startseite: 1 Zugriffe PDF: 14 Zugriffe Startseite: 2 Zugriffe PDF: 10 Zugriffe Startseite: 3 Zugriffe PDF: 10 Zugriffe
Oct
12
Nov
12
Dec
12
Jan
13
Feb
13
Mar
13
Apr
13
May
13
Jun
13
Jul
13
Aug
13
Sep
13
Oct
13
Nov
13
Dec
13
Jan
14
Feb
14
Mar
14
Apr
14
May
14
Jun
14
Jul
14
Aug
14
Sep
14
Monat Oct
12
Nov
12
Dec
12
Jan
13
Feb
13
Mar
13
Apr
13
May
13
Jun
13
Jul
13
Aug
13
Sep
13
Oct
13
Nov
13
Dec
13
Jan
14
Feb
14
Mar
14
Apr
14
May
14
Jun
14
Jul
14
Aug
14
Sep
14
Startseite 11     7 3 6 8 3 2 4 1   3 3 1 1 1 1 1 6   1 2 3
PDF 2 7 9 6 7 5 12 5 4 6 3 4 1 4 1 2 5 7 9 8 9 14 10 10

Gesamtzahl der Zugriffe seit Oct 2012:

  • Startseite – 68 (2.83 pro Monat)
  • PDF – 150 (6.25 pro Monat)
 
 
Generated at 22.10.2014, 11:34:19