WIAS Preprint No. 1256, (2007)

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


Authors

  • Henrion, René
    ORCID: 0000-0001-5572-7213
  • Küchler, Christian
  • Römisch, Werner

2010 Mathematics Subject Classification

  • 90C15

Keywords

  • Stochastic programming, two-stage, mixed-integer, chance constraints,, scenario reduction, discrepancy, Kolmogorov metric

DOI

10.20347/WIAS.PREPRINT.1256

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.

Appeared in

  • J. Indust. Management Optim., 4 (2008) pp. 363--384.

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