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On reducing a quantile optimization problem with discrete distribution to a mixed integer programming problem

  • Stochastic Systems, Queueing Systems
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Abstract

We propose an equivalent reduction of the quantile optimization problem with a discrete distribution of random parameters to a partially integer programming problem of large dimension. The number of integer (Boolean) variables in this problem equals the number of possible values for the random parameters vector. The resulting problems can be solved with standard discrete optimization software. We consider applications to quantile optimization of a financial portfolio and show results of numerical experiments.

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Authors and Affiliations

  1. Moscow State Aviation Institute, Moscow, Russia

    A. I. Kibzun & A. V. Naumov

  2. V.M. Glushkov Institute of Cybernetics, National Academy of Sciences, Kiev, Ukraine

    V. I. Norkin

Authors
  1. A. I. Kibzun
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  2. A. V. Naumov
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  3. V. I. Norkin
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Additional information

Original Russian Text © A.I. Kibzun, A.V. Naumov, V.I. Norkin, 2013, published in Avtomatika i Telemekhanika, 2013, No. 6, pp. 66–86.

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Kibzun, A.I., Naumov, A.V. & Norkin, V.I. On reducing a quantile optimization problem with discrete distribution to a mixed integer programming problem. Autom Remote Control 74, 951–967 (2013). https://doi.org/10.1134/S0005117913060064

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  • DOI: https://doi.org/10.1134/S0005117913060064

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