|edoc-Server der Humboldt-Universität zu Berlin|
Michael Chen, Northwestern University, Evanston|
Sanjay Mehrotra, Northwestern University, Evanston
|Title:||Epi-convergent scenario generation method for stochastic problems via sparse grid|
|Date of Acceptance:||05.04.2008|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Appeared in:||Technical Report 8 (2007)|
|Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.||Endnote Bibtex|
|One central problem in solving stochastic programming problems is to generate moderate-sized scenario trees which represent well the risk faced by a decision maker. In this paper we propose an efﬁcient scenario generation method based on sparse grid, and prove it is epi-convergent. Furthermore, we show numerically that the proposed method converges to the true optimal value fast in comparison with Monte Carlo and Quasi Monte Carlo methods.|
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