Journal article
Placement optimization in refugee resettlement
- Abstract:
- Every year tens of thousands of refugees are resettled to dozens of host countries. 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 decisions. We integrate machine learning and integer optimization into an innovative software tool, Annie Moore, that assists a US resettlement agency with matching refugees to their initial placements. Our software suggests optimal placements while giving substantial autonomy to the resettlement staff to finetune recommended matches, thereby streamlining their resettlement operations. Initial backtesting indicates that Annie can improve short-run employment outcomes by 22%–38%. We conclude by discussing several directions for future work.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, 1.5MB, Terms of use)
-
- Publisher copy:
- 10.1287/opre.2020.2093
Authors
- Publisher:
- INFORMS
- Journal:
- Operations Research More from this journal
- Volume:
- 69
- Issue:
- 5
- Pages:
- 1468-1486
- Publication date:
- 2021-03-24
- Acceptance date:
- 2020-09-21
- DOI:
- EISSN:
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1526-5463
- ISSN:
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0030-364X
- Language:
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English
- Keywords:
- Pubs id:
-
1133164
- Local pid:
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pubs:1133164
- Deposit date:
-
2020-09-21
Terms of use
- Copyright holder:
- INFORMS
- Copyright date:
- 2021
- Rights statement:
- © 2021, INFORMS
- Notes:
- This is the accepted manuscript version of the article. The final version is available from INFORMS at: https://doi.org/10.1287/opre.2020.2093
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