Sanjay Mehrotra, Northwestern University, Evanston
(SPEPS)
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| edoc-Server der Humboldt-Universität zu Berlin |
| Author(s): |
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 |
| Submission Date: | 15.02.2008 |
| Series Title: |
Stochastic Programming E-Print Series (SPEPS) |
| Editors: | Julie L. Higle; Werner Römisch; Surrajeet Sen |
| Appeared in: | Technical Report 8 (2007) |
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| Abstract (eng): | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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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