A Genetic Algorithm Based Examination Timetabling Model Focusing on Student Success for the Case of the College of Engineering at Pamukkale University, Turkey.

This study proposes a genetic algorithm (GA) based model to generate examination schedules such that they focus on students' success in addition to satisfying the hard constraints required for feasibility. The model is based on the idea that the student success is positively related to the adequate preparation and resting time among exams. Therefore, the main objective of this study is to maximize time length among exams (i.e., paper spread) considering the difficulties of exams. Two different genetic algorithm models were developed to optimize paper spread. In the first genetic algorithm model, a high penalty approach was used to eliminate infeasible solutions throughout generations. The second genetic algorithm model controls whether or not each chromosome joining the population satisfies the hard constraints. To evaluate the models, a set of experiments have been designed and studied using the data collected from the College of Engineering in Pamukkale University. [ABSTRACT FROM AUTHOR]