Data-driven management of humanitarian relief incorporating prioritisation

in order to help policymakers to effectively provide humanitarian assistance towards the protection of those ‘most in need’ in difficult humanitarian contexts, We aim to propose a novel framework to support emergency aid allocation and management based on prioritisation schemes that resemble rationing policies. More specifically, we will build an optimisation model to determine robust preparedness decisions regarding which areas must be prioritised given a set of future disaster outcomes, and response decisions on distribution and delivery of emergency aid for each outcome. The prioritisation objective function will be evaluated according to two main concepts: multidimensional deprivation and poverty measure. In our context, multidimensional deprivation refers to the range of deprivation attributes in terms of overall lack of resources and opportunities from which each area is deprived, whereas poverty measure is focused on analysing the (income-shortfall) poverty.