Improving aggregation bounds for two-stage stochastic programs

Improving aggregation bounds for two-stage stochastic programs

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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: ,
Abstract:

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.

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