Discrepancy distances and scenario reduction in two-stage stochastic integer programming

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Date

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1256

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WIAS Preprints

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Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik

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Abstract

Polyhedral discrepancies are relevant for the quantitative stability of mixed-integer two-stage and chance constrained stochastic programs. We study the problem of optimal scenario reduction for a discrete probability distribution with respect to certain polyhedral discrepancies and develop algorithms for determining the optimally reduced distribution approximately. Encouraging numerical experience for optimal scenario reduction is provided.

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