Implementasi Algoritme Ant Colony Optimization untuk Optimasi Rute Distribusi Produk Kebutuhan Pokok dari Toko Sasana Bonafide Mojoroto - Revan Yosua Cornelius Sianturi; Bayu Rahayudi; Agus Wahyu Widodo (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
Efficient work is a profitable job because it is free from certain problems, such as distance problems in the distribution process. Therefore, optimization is one of the solutions that can be relied on as an efficient way to solve a problem, such as the Ant Colony Optimization's algorithm (ACO) in optimizing the distribution route of goods or basic needs products at the Sasana Bonafide store. The optimization problem in this study utilized the concept of the Multi Traveling Salesman Problem (M-TSP) because it involved more than one distributor and had a single depot, which was the Sasana Bonafide store. This study utilized data on customers who lived in 34 different addresses. In this study, ACO succeeded in producing the best solution by combining parameter values to solve the distance optimization problem. The combination of the ACO parameter values utilized in this study, namely the control constant for the intensity of the ant pheromone trail was 1, the visibility control constant was 1, the evaporation constant for the ant pheromone trail was 0.1, and the number of iterations was 500. These parameters were utilized in system testing that tested four times using four different actual data and produced the best solution with each percentage, which was 31.56% produced a distance of 39.4 km, 23.25% produced a distance of 43.52 km, 23.66% produced a distance of 44.14 km, and 25.97% produced a distance of 39.97 km.