Academic Exam Scheduling Using Constraint Satisfaction Solver for Conflict-Free Timetables
Abstract
Academic exam scheduling is a critical task in educational institutions that involves assigning exams to suitable time slots and rooms without conflicts. Effective timetabling ensures fairness and efficiency for both students and administrators. Existing manual or heuristic-based methods often struggle with scalability and complexity, frequently leading to exam overlaps, room capacity violations, and inefficient resource usage. This paper proposes a framework for generating conflict-free academic examination schedules using a Constraint Satisfaction Problem (CSP) Solver. The approach models exams as variables, time slots and rooms as domains, and incorporates constraints such as student conflicts, room capacities, and exam spacing. The CSP solver employs backtracking with heuristics like MRV and forward checking to explore valid schedules efficiently. The system achieves high computational efficiency, generating conflict-free schedules in 1.9 to 13.6 seconds for datasets with 100 to 1000 students, and outperforms alternative methods in accuracy (95–98%), execution speed, and scalability (scalability score: 0.80–0.87). This ensures fairness, resource efficiency, and compliance with institutional constraints.