PENERAPAN METODE ANT COLONY OPTIMIZATION (ACO) DALAM MENENTUKAN JALUR ALTERNATIF SOLUSI KEMACETAN KOTA MEDAN - William William; Rizky Syahputra Sitompul; Adilman Reliance Hia; Roy F. Hasudungan Malau; Saut Parsaoran Tamba; Mohammad Irfan Fahmi (Politeknik Bisnis Indonesia, 2024)
This research aims to analyze and implement the Ant Colony Optimization (ACO) method in determining alternative routes to reduce traffic congestion in Medan City. Against the background of significant congestion problems during rush hours, this research collects traffic data through surveys and observations to serve as input for the ACO algorithm. This method is inspired by the natural behavior of ants in searching for food, where ants collectively find the shortest route based on pheromone trails. Tests were carried out with variations in ACO parameters such as pheromone evaporation rate, number of ants, and iterations to analyze the effectiveness of alternative paths. The research results show that the application of this method can help reduce the burden on the road network and is proven to be able to reduce travel time by 37.5%, where the time needed from 40 minutes can be reduced to 25 minutes. The results of this research can contribute to the development of an intelligent transportation system that is adaptive to changes in traffic conditions and the needs of road users in the city of Medan.