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Improving aggregation bounds for two-stage stochastic programs. (English) Zbl 0955.90097

Summary: 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.

MSC:

90C15 Stochastic programming

Software:

AMPL; OSL; MSLiP
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References:

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