ADAPTIVE EXAMINATION TIMETABLING FOR NIGERIAN UNIVERSITIES: A HYBRID CP-SAT AND GENETIC ALGORITHM OPTIMIZATION SYSTEM WITH HUMAN-IN-THE-LOOP INTEGRATION

To solve scheduling problems in educational institutions with limited resources in Nigeria. This study presents a solution. The problem, modelled as a multi-objective constraint satisfaction problem is solved through a hybrid integration of Genetic Algorithms, Human-in-the-Loop capabilities and Constraint Programming. To enforce the feasibility of hard constraints CP-SAT is used with DEAP genetic algorithms to optimize resource use and to satisfy stakeholders. From spreadsheets that took 4-6 weeks to complete workflows in a single day along with an interactive human-in-the-loop interface that supports real-time adjustments. This study shows how Nigerian University examination scheduling requirements like optimizing carryovers, multi faculty coordination, workload balance and dynamic support can be fulfilled. Evaluation and tests show 99% hard constraint satisfaction in different scenarios and fast processing times from 2.3 minutes for small institutions all the way to 23.4 minutes for large institutions. This research delivers a practical constraint satisfaction problem optimization framework, showing that constraint programming and evolutionary algorithms can be implemented in developing education systems while achieving computational efficiency and institutional compatibility.