Integrating Uncertain Movements into Climate-Induced Refugee Resettlement Planning: A Scenario-Based Two-Stage Stochastic Approach

Abstract

To effectively plan for the large number of refugees that will require resettlement as climate conditions become increasingly critical around the world, decision-makers must be mindful of the current state of resettlement outcomes. We present a mathematical optimization model that can aid in understanding the effects of uncertain unplanned movements on resettlement planning decisions. Such decisions are optimized across two overall scenarios: (i) normal planning conditions and (ii) extreme events occurring as direct or indirect byproducts of climate change (e.g., civil unrest, violent conflict, natural disasters). Within those two scenarios, six nested scenarios represent the best-case, average, and worst-case resettlement success likelihoods. The results of this model indicate the number of resettlement failures a decision-maker should plan to realize, the extra capacity required at each host to accommodate the increased supply at each origin from failed resettlement, and insights into adjustments needing to be made to the planned parameters to recover from continuously low resettlement rates in each of the given planning conditions.