Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10523886 | Operations Research Letters | 2016 | 9 Pages |
Abstract
We derive a lower bound for the sample complexity of the Sample Average Approximation method for a certain class of multistage stochastic optimization problems. In previous works, upper bounds for such problems were derived. We show that the dependence of the lower bound with respect to the complexity parameters and the problem's data are comparable to the upper bound's estimates. Like previous results, our lower bound presents an additional multiplicative factor showing that it is unavoidable for certain stochastic problems.
Related Topics
Physical Sciences and Engineering
Mathematics
Discrete Mathematics and Combinatorics
Authors
M.M.C.R. Reaiche,