Project: academic-guarantee-optimization
Answer Set Programming (ASP)-based tool for optimizing the assignment of academic guarantors to university courses.
Optimization of Academic Guarantors: A Declarative Approach
In collaboration with Simone Colli, this project was presented during the Declarative Programming course (academic year 2024/25) and focused on developing an automated system for assigning academic guarantors to university courses while adhering to ministerial regulations.
Key highlights include:
- Objective: ensuring each course fulfills the required teaching staff quotas, balancing resources efficiently, and meeting minimum standards across various contractual categories.
- Methodology: the problem was modeled using Answer Set Programming (ASP), incorporating rules, facts, and constraints derived from academic and ministerial data. This approach enabled dynamic configuration and adaptation to real-world scenarios.
- Implementation: a robust data preprocessing phase ensured the integration of incomplete or heterogeneous datasets into a standardized ASP framework. Custom rules optimized resource allocation while minimizing reliance on external contracted staff.
- Validation: tested on datasets ranging from small departmental groups to comprehensive university-wide configurations, the system demonstrated scalability and efficiency. Even under computational constraints, the model effectively prioritized tenured and tenure-track faculty over contracted staff, aligning with institutional guidelines.
This project underscores the potential of declarative programming in solving complex resource allocation problems in academia. The full source code and further documentation are accessible via GitHub.
| Code: | GitHub |