Practicable robust stochastic optimization under divergence measures with an application to equitable humanitarian response planning.

We seek to provide practicable approximations of the two-stage robust stochastic optimization model when its ambiguity set is constructed with an -divergence radius. These models are known to be numerically challenging to various degrees, depending on the choice of the -divergence function. The numerical challenges are even more pronounced under mixed-integer first-stage decisions.