Class Scheduling Automation Using Integer Programming: Aligning Professors, Courses, and Time Slots

Abstract

This project addresses the faculty-course-section scheduling problem in an academic institution by employing integer programming techniques to optimize professor assignments while satisfying various constraints. The problem is formulated as an Integer Linear Program (ILP) and solved using the PuLP optimization library. The model considers multiple constraints including professor workload limits, course preferences, section availability, and time-slot assignments. The project is divided two phases: (1) assigning professors to course sections based on preference rankings and workload requirements and (2) scheduling these assignments into available classrooms and time slots while ensuring no conflicts occur. Numerical experiments validate the model’s effectiveness in maximizing professor satisfaction while maintaining feasibility across various scheduling scenarios. The approach provides a scalable and automated alternative to manual scheduling, reducing administrative effort and improving overall scheduling efficiency. Future extensions of this work could involve adding more constraints for better professors satisfaction, assigning recitations or other types of classes that university provide and adapting the model for broader academic scheduling applications.