For a particular class of minimax stochastic programming models, we show that the problem can be equivalently reformulated into a standard stochastic programming problem. This permits the direct use of standard decomposition and sampling methods developed for stochastic programming. We also show that this class of minimax stochastic programs subsumes a large family of mean-risk stochastic programs where risk is measured in terms of deviations from a quantile.

## Citation

Technical report, School of Industrial & Systems Engineering, Georgia Institute of Technology