Cornell University Uses Integer Programming to Optimize Final Exam Scheduling

This paper presents an integer programming-based optimization framework designed to address Cornell University’s complex final exam scheduling challenges. By generating and comparing multiple scheduling variants using Group-then-Sequence and Layer-Cake heuristic approaches, the framework empowers the University Registrar to select schedules that dramatically reduce exam conflicts and enhance student and faculty satisfaction. The models have been successfully implemented at Cornell for several consecutive semesters, demonstrating significant advantages over the historical lecture time-based scheduling method.