We discuss stochastic optimization problems under distributional ambiguity. The distributional uncertainty is captured … estimator in the interior of the resulting confidence region, we propose a new data-driven stochastic optimization problem. This … stochastic optimization problem is bounded by a constant. This constant is small for a sufficiently large i.i.d. sample size and …

supply chain planning model for EMs. To address this research gap, we propose a stochastic optimization model for integrated …