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Decomposition Methods for Two-Stage Stochastic Integer Programs

In: Online Optimization of Large Scale Systems

Author

Listed:
  • Raymond Hemmecke

    (Gerhard-Mercator-Universität Duisburg, Fachbereich Mathematik)

  • Rüdiger Schultz

    (Gerhard-Mercator-Universität Duisburg, Fachbereich Mathematik)

Abstract

Stochastic programs are proper tools for real-time optimization if real-time features arise due to lack of data information at the moment of decision. The paper’s focus is at two-stage linear stochastic programs involving integer requirements. After a discussion of basic structural properties, two decomposition approaches are developed. While the first approach is directed to decomposition of the stochastic program itself, the second deals with decomposition of the related Graver test set.

Suggested Citation

  • Raymond Hemmecke & Rüdiger Schultz, 2001. "Decomposition Methods for Two-Stage Stochastic Integer Programs," Springer Books, in: Martin Grötschel & Sven O. Krumke & Jörg Rambau (ed.), Online Optimization of Large Scale Systems, pages 601-622, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-04331-8_30
    DOI: 10.1007/978-3-662-04331-8_30
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