Matching Algorithms under Diversity-Based Reservations
Haris Aziz, Sean Morota Chu, Zhaohong Sun

TL;DR
This paper conducts a comprehensive comparison of applicant selection algorithms to evaluate their effectiveness in meeting diversity constraints across various real-world scenarios.
Contribution
It provides a detailed analysis of different algorithms' performance in satisfying diversity-based quotas in selection processes.
Findings
Algorithms vary significantly in their ability to meet diversity constraints.
Certain algorithms outperform others in balancing fairness and efficiency.
The study offers insights into selecting appropriate algorithms for diversity-sensitive applications.
Abstract
Selection under category or diversity constraints is a ubiquitous and widely-applicable problem that is encountered in immigration, school choice, hiring, and healthcare rationing. These diversity constraints are typically represented by minimum and maximum quotas on various categories or types. We undertake a detailed comparative study of applicant selection algorithms with respect to the diversity goals.
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Taxonomy
TopicsScheduling and Timetabling Solutions · Game Theory and Voting Systems · Optimization and Search Problems
