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Stochastic Programming: Solution Techniques and Approximation Schemes

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Mathematical Programming The State of the Art

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Abstract

Solutions techniques for stochastic programs are reviewed. Particular emphasis is placed on those methods that allow us to proceed by approximation. We consider both stochastic programs with recourse and stochastic programs with chance-constraints.

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Authors and Affiliations

  1. Department of Mathematics, University of Kentucky, Lexington, Kentucky, 40506, USA

    R. Wets

  2. I.IA.S.A, 2361, Laxenburg, Austria

    R. Wets

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  1. R. Wets
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Editors and Affiliations

  1. Institut für Ökonometrie und Operations Research, Universität Bonn, Nassestraße 2, D-5300, Bonn 1, Germany

    Achim Bachem  & Bernhard Korte  & 

  2. Lehrstuhl für Angewandte Mathematik II, Universität Augsburg, Memminger Straße 6, D-8900, Augsburg, Germany

    Martin Grötschel

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Wets, R. (1983). Stochastic Programming: Solution Techniques and Approximation Schemes. In: Bachem, A., Korte, B., Grötschel, M. (eds) Mathematical Programming The State of the Art. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-68874-4_22

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  • DOI: https://doi.org/10.1007/978-3-642-68874-4_22

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