Ant Colony Optimization for a Plan Guide Course Registration Sequence

Abstract

Students in universities do not follow the prescribed course plan guide, which affects the registration process. In this research, we present an approach to tackle the problem of guide for plan of course sequence (GPCS) since that sequence may not be suitable for all students due to various conditions. The Ant Colony Optimization (ACO) algorithm is anticipated to be a suitable approach to solving such problems. Data on sequence of the courses registered by students of the Computer Science Department at Al Al-Bayt University over four years were collected for this study. The fundamental task was to find the suitable pheromone evaporation rate in ACO that generates the optimal GPCS by conducting an Adaptive Ant Colony Optimization (AACO) on the model that used the collected data. We found that 17 courses out of 31 were placed in semesters differing from the semesters preset in the course plan.