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Numerical Techniques in Applied Multistage Stochastic Programming

  • Karl Frauendorfer
  • Gido Haarbrücker
Chapter
  • 351 Downloads
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 59)

Abstract

This contribution deals with the apparent difficulties when solving an optimization problem with random influences by the use of multistage stochastic linear programming. It names specific numerical solution techniques which are suitable for coping with the curse of dimensionality, with increasing scenario trees and associated large-scale LPs. The focus lies on classic decomposition methods which are natural candidates to apply parallelization techniques. In addition, an alternative approach is sketched where the replacement of optimization runs by optimality checks leads to an efficient handling of consecutive discretization steps given some structural requirements arc fulfilled.

Keywords

Multistage stochastic linear programming discretization large-scale linear program numerical techniques 

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Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Karl Frauendorfer
    • 1
  • Gido Haarbrücker
    • 1
  1. 1.Institute for Operations ResearchUniversity of St. GallenSwitzerland

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