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

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

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Article ID: iaor20133963
Volume: 74
Issue: 6
Start Page Number: 951
End Page Number: 967
Publication Date: Jun 2013
Journal: Automation and Remote Control
Authors: , ,
Keywords: control
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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