Article ID: | iaor20043780 |
Country: | Netherlands |
Volume: | 24 |
Issue: | 3 |
Start Page Number: | 127 |
End Page Number: | 137 |
Publication Date: | Apr 1999 |
Journal: | Operations Research Letters |
Authors: | Rosa Charles H., Takriti Samer |
Stochastic multi-stage linear programs are rarely used in practical applications due to their size and complexity. Using a general matrix to aggregate the constraints of the deterministic equivalent yields a lower bound. A similar aggregation in the dual space provides an upper bound on the optimal value of the given stochastic program. Jensen's inequality and other approximations based on aggregation are a special case of the suggested approach. The lower and upper bounds are tightened by updating the aggregating weights.