Application of Greedy Algorithm and Simulated Annealing Algorithm on the Asymmetric Capacitated Vehicle Routing Problem Model in Designing Optimal Garbage Transportation Routes - Bella Arisha; Fitri Maya Puspita; Bambang Suprihatin; Indrawati (Vokasi UNESA Bulletin of Engineering, Technology and Applied Science, 2026)
Waste management remains a recurring issue, particularly in large urban areas. An optimal waste collection route is essential to prevent the problem from becoming more severe and persistent. This study aims to determine the minimum distance and route for waste collection in the Seberang Ulu 1 District, Palembang, using the Greedy and Simulated Annealing algorithms. The calculations were carried out by dividing the district into four work zones. The results show that, using the Greedy algorithm, the minimum distances and routes for work zones 1 through 4 were 24.655 km, 29.7 km, 22.7 km, and 24.705 km, respectively. Meanwhile, using the Simulated Annealing algorithm, the minimum distances and routes for each work zone were 24.325 km, 32.45 km, 22.5 km, and 22.385 km. On average, SA reduces the total distance traveled by 2.1% compared to Greedy, but it requires a longer computation time due to its iterative process of finding the global optimum. These indicate that both algorithms are equally effective in solving the ACVRP problem, with different advantages. SA's advantage in optimizing more complex routes and Greedy's advantage in computation speed for practical implementation. These findings indicate that the Simulated Annealing Algorithm and the Greedy Algorithm almost the same results in solving the Asymmetric Capacitated Vehicle Routing Problem in Seberang Ulu 1 District, Palembang.