Optimasi Vehicle Routing Problem (VRP) Terhadap Rute Pengangkutan Sampah Di Kota Medan Dengan Algoritma Ant Colony Optimization - Kinanti, Tri; Rima Aprilia (Mandalika Mathematics and Educations Journal, 2025)
The growing population in Medan City has resulted in a significant increase in waste volume, creating the need for an efficient transportation system from Temporary Disposal Sites (TPS) to the Final Disposal Site (TPA). This study aims to apply the Ant Colony Optimization (ACO) algorithm to improve the efficiency of waste collection routes in the Medan Marelan District. ACO is a metaheuristic algorithm inspired by the foraging behavior of ants, where pheromone trails guide route selection. In this research, TPS and TPA locations were divided into six zones. Each zone was analyzed to determine the most efficient route based on the shortest travel distance. The research methodology consists of two main phases: route construction and pheromone updating. Data analysis was conducted manually for the first zone and through computational simulations using Python for the remaining five zones. The results show that ACO effectively produced optimal waste transportation routes in all areas. The shortest routes obtained were: Zone 1 at 17.05 km, Zone 2 at 25.25 km, Zone 3 at 16.995 km, Zone 4 at 8 km, Zone 5 at 14.83 km, and Zone 6 at 11.5 km. These findings confirm that the ACO algorithm is effective in addressing the Vehicle Routing Problem (VRP) in the context of waste transportation and offers a promising approach for enhancing urban waste management systems.