"Automating Course Scheduling with Linear Programming and the Python Pu" by George K. Thiruvathukal
 

Document Type

Presentation

Publication Date

4-22-2025

Publication Title

Figshare

Abstract

This article presents a pragmatic approach to automating course scheduling in an academic setting using linear programming.

We explore how linear optimization via current open-source tools can efficiently handle scheduling constraints such as instructor preferences, teaching loads, course section requirements, and specific time slots. Using Python’s PuLP library and matplotlib for visualization, we built a flexible and accessible scheduling system.

Our research prototype balances course assignments while addressing department-specific needs, demonstrating how linear programming can simplify academic scheduling and improve efficiency.

Although this is a research prototype, our results already demonstrate the ability to generate a correct course schedule that ensures all constraints are met and can easily be adapted to support on-the-ground course scheduling changes.

Comments

Author Posting © The Author(s), 2025.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Share

COinS