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Abstract

Tens of thousands of refugees are resettled yearly from refugee camps to host countries. Local areas that host refugees are reluctant to open capacity, and most impose tight restrictions on the refugee family types they accept. We model this matching challenge as a 0-1 knapsack variant and explore outcomes-related objectives in the search toward an optimal allocation. Our employment optimization matching problem is embedded within a dynamic software tool that facilitates interactive use to fine-tune the recommended match results. We estimate counterfactual employment outcome improvement to be 22%-37%.

Speaker Bio

Andrew C. Trapp is Associate Professor of Operations and Industrial Engineering at Worcester Polytechnic Institute (WPI), with courtesy professorships in Mathematical Sciences and Data Science. His research centers on using prescriptive (integer optimization) and predictive (machine learning) analytics, together with algorithms, to effectively allocate scarce resources – especially for the benefit of vulnerable and marginalized individuals, groups, and populations. His research is supported by the US National Science Foundation (Operations Engineering) grants CMMI-1825348, CMMI-1841893, CMMI-1935602, the Ragnar Söderberg Foundation, and others. He publishes in journals such as Operations Research, INFORMS Journal on Computing, European Journal of Operational Research, IISE Transactions, Discrete Optimization, and Decision Support Systems. More information can be found on his website: http://users.wpi.edu/~atrapp/

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The Operations Research (OR) seminar series brings together graduate students, faculty and researchers from the University of Toronto community to interact with prominent scholars in the field of OR. Seminars feature visiting scholars from around the world as well as professors and post-docs. Topics include all variants of OR theory and their applications. Questions? Contact Merve Bodur at bodur@mie.utoronto.ca