The Course Schedule Optimizer is a Python-based tool paired with Gurobi Optimizer, designed to streamline and enhance the course scheduling process for Berry College’s School of Mathematics and Natural Sciences (MNS). This application helps faculty and academic advisors detect scheduling conflicts and provides recommendations to optimize course arrangements, reducing manual workload and minimizing errors.
- Recommendation Engine with Gurobi Optimizer: Using Gurobi Optimizer in Python, this program suggests course rearrangements to resolve identified conflicts. This model serves as a proof of concept for creating an efficient, conflict-free schedule with minimal manual adjustments.
- Programming Language: Python
- Libraries:
pandasfor handling and manipulating Excel-based schedulesgurobipyfor implementing optimization algorithms with Gurobi
The project envisions a fully integrated scheduling solution that combines conflict detection and optimization, creating a streamlined and standardized process for MNS faculty. By automating and optimizing schedule generation, this tool aims to reduce faculty workload and establish a reliable scheduling framework for the future.
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To Dr. Cochran, for your unwavering patience, kindness, and intentionality. Your support, guidance, and encouragement have been invaluable in making this achievement possible. I am deeply grateful to have you as my advisor, professor, and friend.
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To Dr. Hamid, for nurturing my appreciation for computer science and problem-solving. Your gentleness, attention to detail, and passion for your field and your students have played a pivotal role in shaping my academic and personal journey.