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\end{itemize}   Hence, it is crucial to devote independent efforts to study the uncertainty and its impacts in humanitarian logistics.  ``Mathematical programming'', ``Probability and Statistics'', and ``Simulation'' are a few of the widely-used approaches to study humanitarian logistics problems. Among the aforementioned approaches, mathematical programming has attracted the most attention of OR community over the last decade \cite{RahaAkhavanORModelsSurvery}. In particular, several optimization problems under uncertainty have been studied that arise in response planning, preparedness planning, mitigation planning, etc. The reader is advised to refer to \cite{, , } \cite{,,}  for further details in this regard. Several approaches to incorporate the uncertainty within optimization problems have been proposed since the realization of the need adopt more realistic mathematical programs. In particular, the majority of the efforts have been devoted to one of the two most prominent paradigms: 1) stochastic programs, and 2) robust optimization problems. While the latter emphasizes on the importance of immunization against the worst-case scenario, the former is more focused on the expected costs in the long-run. Also, while the robust optimization paradigm has attracted the researchers' attention over the last two decades, the stochastic programming is one of the first approaches to study uncertain mathematical programs and have been widely used in the literature.