NETWORK MODELS FOR THE HUMAN MIGRATION PHENOMENON

Abstract. Large-scale migration flows are posing immense challenges for governments around the globe, with drivers ranging from climate change and disasters to wars, violence, and poverty. In this work we introduce and analyze four different multiclass human migration network models under both user-optimizing and system-optimizing approaches. Different scenarios are proposed: in one model policy intervention, in the form of subsidies, allows governmental decision-makers to moderate the flow of migrants while enhancing societal welfare; in another model the locations associated with migration are subject to capacities; in another one we introduce regulations inspired by the Covid-19 pandemic and with the explicit inclusion of migration costs. The formulation and analysis are conducted using tools of Game theory and of variational inequality theory. Lagrange analysis is also performed in order to obtain a precise evaluation of the multiclass human migration phenomenon. Some numerical examples complete the thesis.