Deploying Fair and Efficient Course Allocation Mechanisms

With Cyrus Cousins, George Bissias and Yair Zick

In large universities, the task of assigning classes to thousands of students while considering their preferences, along with course schedules and capacities, presents a significant challenge. Ensuring the effectiveness and fairness of course allocation mechanisms is crucial to guaranteeing student satisfaction and optimizing resource utilization. We address this problem from an economic perspective, using formal justice criteria to evaluate different algorithmic frameworks. We develop software for generating synthetic students with binary preferences over courses represented by linear inequality constraints, and implement four allocation algorithms: the Default algorithm used by Anonymous University; Round Robin; an Integer Linear Program; and the Yankee Swap algorithm, a flexible approach that offers significant fairness guarantees. We propose improvements to the Yankee Swap framework to handle scenarios with item multiplicities. Through experimentation with the Fall 2024 Computer Science course schedule at Anonymous University, we evaluate each algorithm’s performance relative to standard justice criteria, providing insights into fair course allocation in large university settings.

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