A Novel Traffic Routing Method Using Hybrid Ant Colony System Based on Genetic Algorithm

The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm. It is very famous with Traveling Salesman Problem. The parameters of ACS in tour construction, global and local updating pheromone direct effort to get the best result of this but they are often manually setting up. Beside, building the heuristic function to decide a choice next node on tour is potential research approach. Therefore, this paper present a foundation framework that propose a novel method to solve traffic routing problem by hybrid ant colony system (ACS) based on genetic algorithm, visualization online changing traffic light, it is called (GACSS). In the GACSS, We use genetic algorithm (GA) optimize ACS parameters aim to attain shortest trips and time with new functions helping them to update global and local pheromone. Our experiment with GACSS deploys in VANETsim with real map from open street map project, any vehicle kind and updating traffic light real-time able. Our framework gained higher results than A-Star and classical ACS algorithm. It is not only shorter length but also smaller time for trip.