Abstract
The World Bank estimates that the number of refugees worldwide will reach 140 million by 2050 due to global warming and local wars. Considering the rapid increase in the number of refugees, an efficient and feasible assignment method is required for refugee resettlement. This article formalizes the refugee resettlement issue using the Environments-Classes, Agents, Roles, Groups, and Objects (E-CARGO) model. A novel solution is designed for Refugee reSettling (RS) by extending the Group MultiRole Assignment (GMRA), which applies the agent stability evaluation method as a feedback mechanism while optimally resettling refugees. With this proposed solution, decision-makers can swiftly resettle refugees from multiple suffering countries while appropriately ensuring host countries’ benefit. Finally, large-scale simulation experiments based on the Python PuLP platform are carried out to demonstrate the practicability and robustness of the proposed solution. The simulation results provide a solid decision-making reference for the leaders of the world.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
