This study provided a means of optimizing air transport routes for Air Force, using agent-based modeling. To improve the routes, we modified routes (TOBE model) using our heuristic algorithm. Using the real air transportation data collected by Air Force Logistics Command, we made transport demand as random variables. To compare the current route (ASIS model) and the TOBE model, the Monte Carlo simulation performed 100 times the same demand. Comparison of the simulation results of the ASIS model and the TOBE model was compared with the total flight distance, freight and traffic volume. The simulation results shows that the total flight distance of the TOBE model decreased by about 22.31% compared to the ASIS model, and the freight traffic volume decreased by about 0.5% and the traffic volume increased by approximately 0.7%. These results can be used to establish future Air Force and will help improve the air transport routes to achieve higher performance than current routes.


Agent based modeling, Vehicle routing problem, Air transport, Heuristic, Algorithm