Cornell University Uses Integer Programming to Optimize Final Exam Scheduling

TL;DR

This paper introduces an integer programming framework for optimizing final exam schedules at Cornell University, effectively handling complex constraints and improving over traditional methods to save time and increase satisfaction.

Contribution

It presents a flexible integer programming approach with heuristic enhancements for exam scheduling, tailored to university constraints and decision-making needs.

Findings

Significant time and effort savings achieved.

Improved student and faculty satisfaction.

Outperforms historical scheduling methods.

Abstract

This paper presents an integer programming-based optimization framework designed to effectively address the complex final exam scheduling challenges encountered at Cornell University. With high flexibility, the framework is specifically tailored to accommodate a variety of different constraints, including the front-loading of large courses and the exclusion of specific time slots during the exam period. By generating multiple scheduling model variants and incorporating heuristic approaches, our framework enables comprehensive comparisons of different schedules. This empowers the University Registrar to make informed decisions, considering trade-offs in terms of schedule comfort measured by different levels of exam conflicts. Our results demonstrate significant advantage over the historical lecture time-based approach, providing time and effort savings for the university administration while enhancing student and faculty satisfaction.