The exam scheduling algorithm uses a genetic algorithm approach to find an optimal solution while respecting all constraints:

• Hard Constraints: These must be satisfied for a schedule to be valid:
  • No classroom can be used for multiple exams at the same time on the same date
  • No teacher can supervise multiple exams at the same time on the same date
  • Classroom capacity must be sufficient for the number of students
  • Teacher availability constraints must be respected
  • Holiday constraints must be respected (no exams on holidays)
  • No exams on weekends
  • Time slot day must match the day of the week of the scheduled date
• Soft Constraints: These are preferred but not required:
  • Even distribution of exams across available days
  • Optimal classroom utilization (not too empty, not too full)
  • Minimize consecutive exams for teachers

The algorithm generates multiple potential schedules, evaluates them based on constraint satisfaction and optimization criteria, and evolves better solutions over multiple generations. The final schedule is the best solution found within the computational limits.

Quality scores are calculated based on how well the schedule satisfies both hard and soft constraints, with a maximum score of 150 points.

The algorithm utilizes the full date range specified in the exam period, distributing exams across all available days (excluding weekends and holidays) to create a comprehensive schedule.