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2008-04-05Buch DOI: 10.18452/8391
Epi-convergent scenario generation method for stochastic problems via sparse grid
Chen, Michael
Mehrotra, Sanjay
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 comparisonwith Monte Carlo and Quasi Monte Carlo methods.
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DOI
10.18452/8391
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