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Refugee resettlement via machine learning and integer optimization

Trapp, Andrew C.; Teytelboym, Alexander; Ahani, Narges and Andersson, Tommy LU (2018) 60th Annual Conference of the Operational Research Society, OR 2018 p.21-26
Abstract

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.

Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Humanitarian operations research, Integer optimization, Machine learning, Matching, Multiple multidimensional knapsack problem, Refugees
host publication
OR60
editor
Kheiri, Ahmed and
pages
6 pages
publisher
OR Society
conference name
60th Annual Conference of the Operational Research Society, OR 2018
conference location
Lancaster, United Kingdom
conference dates
2018-09-11 - 2018-09-13
external identifiers
  • scopus:85060549262
ISBN
9780903440646
language
English
LU publication?
yes
id
352e624e-f840-45ec-9f91-d6cda2c8fe3a
date added to LUP
2019-02-11 08:31:31
date last changed
2019-02-27 05:13:15
@inproceedings{352e624e-f840-45ec-9f91-d6cda2c8fe3a,
  abstract     = {<p>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.</p>},
  author       = {Trapp, Andrew C. and Teytelboym, Alexander and Ahani, Narges and Andersson, Tommy},
  editor       = {Kheiri, Ahmed},
  isbn         = {9780903440646},
  keyword      = {Humanitarian operations research,Integer optimization,Machine learning,Matching,Multiple multidimensional knapsack problem,Refugees},
  language     = {eng},
  location     = {Lancaster, United Kingdom},
  pages        = {21--26},
  publisher    = {OR Society},
  title        = {Refugee resettlement via machine learning and integer optimization},
  year         = {2018},
}