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Portrait of Tommy Andersson. Photo.

Tommy Andersson

Professor

Portrait of Tommy Andersson. Photo.

Refugee resettlement via machine learning and integer optimization

Author

  • Andrew C. Trapp
  • Alexander Teytelboym
  • Narges Ahani
  • Tommy Andersson

Editor

  • Ahmed Kheiri

Summary, in English

Around 100,000 refugees are resettled to dozens of countries from conflict zones every year. While there is growing evidence that the initial placement of refugee families profoundly affects their lifetime outcomes, there have been few attempts to optimize resettlement destinations within host countries. We describe how machine learning and integer optimization can be used to empower resettlement agencies to drastically improve refugee employment outcomes. We describe possible future work on multi-objective optimization, the dynamics of allocation, and the inclusion of refugee preferences.

Department/s

  • Department of Economics

Publishing year

2018

Language

English

Pages

21-26

Publication/Series

OR60 : The OR Society Annual Conference

Document type

Conference paper

Publisher

OR Society

Topic

  • Political Science (excluding Public Administration Studies and Globalization Studies)
  • Information Systems

Keywords

  • Humanitarian operations research
  • Integer optimization
  • Machine learning
  • Matching
  • Multiple multidimensional knapsack problem
  • Refugees

Conference name

60th Annual Conference of the Operational Research Society, OR 2018

Conference date

2018-09-11 - 2018-09-13

Conference place

Lancaster, United Kingdom

Status

Published

ISBN/ISSN/Other

  • ISBN: 9780903440646