Dealing with migratory flows under uncertainty: a multi-objective optimization approach

Abstract

Nowadays, managing migratory flows has become one of the most relevant challenges for politicians in the recipient countries. However, the estimation of those inflows has turned into a complex problem given both the plethora of variables driving them and the multiple interactions among drivers.This paper presents a tool to help governments forecast immigration flows by combining simulation and fuzzy logic techniques. This approach allows dealing with the uncertainty arisen from the scarce data available, but also results into a multi-objective optimization problem regarding to the fitting of the model parameters. To tackle it, an evolutionary algorithm is designed for this task. The proposal is used to evaluate the Ecuadorian inflows to Spain during the last decade. The results are consistent with those previously obtained by expert-knowledge elicitation while providing some useful insights for national migratory policy design.