Daniel Kuhn, Wolfram Wiesemann
Stochastic programming provides a versatile framework for decision-making under uncertainty, but the resulting optimization problems can be computationally demanding. It has recently been shown that, primal and dual linear decision rule approximations can ...
Springer Verlag2015