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On Solution of Stochastic Linear Programs by Discretization Methods

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Stochastic and Global Optimization

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 59))

Abstract

Stochastic linear programs (SLP) with complete fixed recourse are solved approximatively by means of discretization of the underlying probability distribution of the random parameters. Error estimates are given, and a priori bounds for the approximation error are derived. Furthermore, exploiting invariance properties of the probability distribution of the random parameters, problem-oriented discretizations are derived which simplify then the computation of admissible descent directions at non-stationary points.

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Bibliography

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Author information

Authors and Affiliations

  1. Aero-Space Engineering and Technology, Federal Armed Forces University, D-85577, Neubiberg, München, Germany

    K. Marti

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  1. K. Marti
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Editor information

Editors and Affiliations

  1. Institute of Mathematics and Informatics, Vilnius, Lithuania

    Gintautas Dzemyda , Vydūnas Šaltenis  & Antanas Žilinskas ,  & 

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© 2002 Kluwer Academic Publishers

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Marti, K. (2002). On Solution of Stochastic Linear Programs by Discretization Methods. In: Dzemyda, G., Šaltenis, V., Žilinskas, A. (eds) Stochastic and Global Optimization. Nonconvex Optimization and Its Applications, vol 59. Springer, Boston, MA. https://doi.org/10.1007/0-306-47648-7_11

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  • DOI: https://doi.org/10.1007/0-306-47648-7_11

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-0484-1

  • Online ISBN: 978-0-306-47648-8

  • eBook Packages: Springer Book Archive

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