|edoc-Server der Humboldt-Universität zu Berlin|
Christian Küchler, Mathematik|
Stefan Vigerske, Mathematik
|Title:||Numerical Evaluation of Approximation Methods in Stochastic Programming|
|Date of Acceptance:||02.07.2008|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10090091)|
|Keywords (eng):||scenario tree, multistage stochastic programming, out-of-sample evaluation|
|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.|
|We study an approach for the evaluation of approximation and solution methods for multistage linear stochastic programs by measuring the performance of the obtained solutions on a set of out-of-sample scenarios. The main point of the approach is to restore the feasibility of solutions to an approximated problem along the out-of-sample scenarios. For this purpose, we consider and compare different feasibility and optimality based projection methods. With this at hand, we study the quality of solutions to different test models based on classical as well as recombining scenario trees.|
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: