Algoritma Ant Colony Optimization untuk Optimasi Penjadwalan Mata Kuliah
Ant Colony Optimization Algorithm for Lecturing Schedule Optimization
The purpose of this study is to optimize the the lecturing schedule using the Ant Colony Optimization (ACO) algorithm. The method developed will find an optimal solution of lecturing schedule where there are some limitations that must be considered. These limitations include being a lecturer or a class that can only be scheduled to lecture a maximum of two times in a row. Another limitation is that two adjacent level may not be scheduled at the same time, because there is a possibility that students will repeat a lecture. The third limitation is that there should be no lecturers or classes that conduct lectures with too high a frequency one day. And the fourth limitation is the alternative time where lecturers can teach will be limited due to other activities that must be carried out by the lecturer. So that the course scheduling case can be solved using the ACO algorithm, a graph is made where each node is the name of the course that must be scheduled. The path created by the ants from the initial node to the end node will contain the order of courses that must be carried out one week. Based on the test results, the ACO algorithm has succeeded in scheduling courses involving 38 subjects, 4 class forces, 6 recovery locations and 12 lecturers supporting the courses. The scheduling solution obtained has a fitness value of 0.0092. Where there are no lecturers who have a high teaching frequency one day, but there are 12 class schedules that cause a class to follow a high frequency of lectures. And there are 4 courses scheduled to be close together. This final performance is considered quite good and shows that ACO has been successfully used to optimize course scheduling.