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    Discrepancy distances and scenario reduction in two-stage stochastic integer programming
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2007) Henrion, René; Küchler, Christian; Römisch, Werner
    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.