Matching Algorithms under Diversity-Based Reservations

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.