Pheromone-Guided University Timetable Construction Using Ant Colony Optimization: A Case Study

University course timetabling is a non-deterministic polynomial time-hard (NP-hard) problem that involves assigning courses to times and venues while satisfying constraints and minimizing violations. This task is especially challenging for specific institutions. In this work, we introduce an enhanced Ant Colony Optimization (ACO) approach, called the University Course Timetabling Problem Ant System (UCTP-AS), designed to address these complexities proficiently. It uses priority-based courses to prioritize courses based on enrolment of student batches, violation-aware heuristics to guide the search toward feasible solutions, and explicit soft constraint integration to actively consider soft constraints during timetabling construction. The integration of pheromone trails, heuristic information, and these strategic mechanisms enables the UCTP-AS to effectively navigate the search space and generate high-quality timetables. Tested on the FCSIT 2018/2019 dataset, UCTP-AS produces feasible timetables with an 11 % to 13 % variation in solutions across four different iteration conditions. It can generate near-optimal timetables with as few as four violations (HC=O, SC=4), especially with longer iterations. Even in shorter runs, it consistently finds feasible timetables. These results suggest that UCTP-AS is a promising approach for tackling complex university timetabling challenges in practical settings.