Solving University Course Timetabling Problem Using Ant Colony Optimization: An Example of Mersin University Engineering Faculty
AbstractBuilding effective schedules in academical institutions considering the wishes and needs of administrative staff, professors and students at the same time is a rather difficult and time-consuming activity for staff involved in this work. Despite improvements in software and hardware technology in recent years, charts are still manually created in many educational institutions and the desired efficiency has not achieved. In this study, the course chart of Mersin University Engineering Faculty was built using Ant Colony Optimization (ACO) technique. While the course schedule was being formed, 9 departments, 24 common classrooms, 105 faculty members, 239 courses, 14.374 students who have attendance obligations and 8286 students who have not attendance obligations were taken into consideration. In the placement of the courses, adaptation to ACO algorithm has been achieved by targeting the maximum lecture minimum classroom usage. The appropriate hours of the lecturers were accepted as strict constraints and other cases were added to soft constraints. All courses of Mersin University Engineering Faculty have placed the course schedule to appropriate classrooms at the rate of 99% using ACO technique, and 17 classrooms of common 24 classrooms were determined to be sufficient for educational activities.