An approximation framework for two-stage ambiguous stochastic integer programs under mean-MAD information.

•We propose a framework to solve two-stage problems under distributional ambiguity.•Our method accounts for integer recourse decisions in two-stage problems.•We provide bounds on the approximation quality in case of integer recourse.•Our framework allows to quantify the value of distributional information.