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Upper bounds for Gaussian stochastic programs

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Abstract.

We present a construction which gives deterministic upper bounds for stochastic programs in which the randomness appears on the right–hand–side and has a multivariate Gaussian distribution. Computation of these bounds requires the solution of only as many linear programs as the problem has variables.

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Author information

Authors and Affiliations

  1. Dept. of Statistics, University of Auckland, Private Bag 92019, Auckland, New Zealand, e-mail: pritchar@scitec.auckland.ac.nz., , , , , , NZ

    Geoffrey Pritchard

  2. Department of Engineering Science, University of Auckland, Private Bag 92019, Auckland, New Zealand, e-mail: g.zakeri@auckland.ac.nz., , , , , , NZ

    Golbon Zakeri

Authors
  1. Geoffrey Pritchard
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  2. Golbon Zakeri
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Received December 2, 1997 / Revised version received January 5, 1999¶ Published online May 12, 1999

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Pritchard, G., Zakeri, G. Upper bounds for Gaussian stochastic programs. Math. Program. 86, 51–63 (1999). https://doi.org/10.1007/s101070050079

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  • DOI: https://doi.org/10.1007/s101070050079