Automated course scheduler for Ashesi University College

Abstract

Ashesi University College is faced with the challenge of effectively scheduling courses at the beginning of the semester so that there are no class clashes for both lecturers and students. In an attempt to solve the Course Timetabling Problem at Ashesi University College, five algorithms: Genetic Algorithm, Constraint Programing, Particle Swarm Optimization, Simulated Annealing and Tabu Search algorithm, which are known for their use in solving University Course Timetabling problems have been studied and based on their ease of implementation, their robustness in arriving at feasible solutions, their computational speed and whether an optimal solution is always guaranteed, Particle Swarm Optimization algorithm is chosen to implement a solution to the Ashesi University Course Timetabling problem. This project is focused on eliminating course conflicts and creating an optimal table based on teachers‟ preferences for certain timeslots to teach during the week. The paper outlines the assumptions and steps including explanations on Particle Swarm Optimization used in constructing the timetable base on teachers‟ preferences. Test conducted on the project proved that the use of Particle Swarm Optimization to solve the Ashesi Course Timetabling problems is in the right direction.Finally, the paper proposes a focus on other areas of the course timetabling problem at Ashesi University College, using the same Particle swarm optimization procedures described in the paper to help provide a complete solution to the timetabling problem of the school.