TITLE:
Explicit Artificial Intelligence Timetable Generator for Colleges and Universities
AUTHORS:
Lawrence A. Farinola, Mahougnon B. M. Assogba
KEYWORDS:
Genetic Algorithm, AI Timetabling, Automatic Scheduling, Constraint Satisfaction, Optimization
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.15 No.8,
August
15,
2025
ABSTRACT: Manual timetable preparation in colleges and universities is often time-consuming, error-prone, and inefficient, especially with increasing student and course complexity. This paper proposes an Explicit Artificial Intelligence-based Timetable Generator that leverages a Genetic Algorithm to automatically generate conflict-free, optimized academic schedules. The system incorporates user-defined constraints and priorities such as room availability, lecturer-course assignments, and course clash avoidance. Extensive testing was conducted using real-world institutional data to evaluate the system’s effectiveness. The proposed approach significantly reduced scheduling time, eliminated course conflicts, and improved allocation efficiency across multiple views, including per lecturer, per student, and per classroom. The results demonstrate the system’s scalability and practical viability for higher education environments.