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Stochastic Programming 84 Part I pp 183–190Cite as

An alternating method for stochastic linear programming with simple recourse

Part of the Mathematical Programming Studies book series (MATHPROGRAMM,volume 27)

Abstract

Stochastic linear programming with simple recourse arises naturally in economic problems and other applications. One way to solve it is to discretize the distribution functions of the random demands. This will considerably increase the number of variables and will involved discretization errors. Instead of doing this, we describe a method which alternates between solving some n-dimensional linear subprograms and some m-dimensional convex subprograms, where n is the dimension of the decision vector and m is the dimension of the random demand vector. In many cases, m is relatively small. This method converges in finitely many steps.

Keywords

  • Stochastic Programming
  • Computer Science Department
  • Certainty Equivalent
  • Stochastic Demand
  • Decision Vector

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Sponsored by the National Science Foundation under Grant No. MCS-8200632.

Current address: Department of Mathematics and Statistics, University of Pittsburgh, Pittsburgh, PA 15260, USA.

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Author information

Authors and Affiliations

  1. International Institute for Applied Systems Analysis, Schloss Laxenburg, A-2361, Laxenburg, Austria

    Liqun Qi

  2. Computer Sciences Department, University of Wisconsin-Madison, 53706, Madison, WI, USA

    Liqun Qi

Authors
  1. Liqun Qi
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Editor information

Andras Prékopa Roger J.- B. Wets

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© 1986 The Mathematical Programming Society, Inc.

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Qi, L. (1986). An alternating method for stochastic linear programming with simple recourse. In: Prékopa, A., Wets, R.J.B. (eds) Stochastic Programming 84 Part I. Mathematical Programming Studies, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0121120

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  • DOI: https://doi.org/10.1007/BFb0121120

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00924-2

  • Online ISBN: 978-3-642-00925-9

  • eBook Packages: Springer Book Archive

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