TY - GEN A1 - Henrion, Rene A1 - Küchler, Christian A1 - Römisch, Werner T1 - Scenario reduction in stochastic programming with respect to discrepancy N2 - Discrete approximations to chance constrained and mixed-integer two-stage stochastic programs require moderately sized scenario sets. The relevant distances of (multivariate) probability distributions for deriving quantitative stability results for such stochastic programs are $\mathcal{B}$-discrepancies, where the class $\mathcal{B}$ of Borel sets depends on their structural properties. Hence, the optimal scenario reduction problem for such models is stated with respect to $\mathcal{B}$-discrepancies. In this paper, upper and lower bounds, and some explicit solutions for optimal scenario reduction problems are derived. In addition, we develop heuristic algorithms for determining nearly optimally reduced probability measures, discuss the case of the cell discrepancy (or Kolmogorov metric) in some detail and provide some numerical experience. KW - Stochastic programming KW - chance constraints KW - two-stage KW - mixed-integer KW - scenario reduction KW - discrepancy KW - Kolmogorov metric Y1 - 2006 UR - https://opus4.kobv.de/opus4-matheon/frontdoor/index/index/docId/361 UR - https://nbn-resolving.org/urn:nbn:de:0296-matheon-3618 ER -