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A Hybrid Method Based on Genetic Algorithm and Ant Colony System for Traffic Routing Optimization


Thi-Hau Nguyen, Ha-Nam Nguyen, Dang-Nhac Lu, and Duc-Nhan Nguyen


Vol. 23  No. 8  pp. 85-90


The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm which is well-known in Traveling Salesman Problem. This paper proposed a hybrid method based on genetic algorithm (GA) and ant colony system (ACS), called GACS, to solve traffic routing problem. In the GACS, we use genetic algorithm to optimize the ACS parameters that aims to attain the shortest trips and time through new functions to help the ants to update global and local pheromones. Our experiments are performed by the GACS framework which is developed from VANETsim with the ability of real map loading from open street map project, and updating traffic light in real-time. The obtained results show that our framework acquired higher performance than A-Star and classical ACS algorithms in terms of length of the best global tour and the time for trip.


Traffic routing; ant colony system; genetic algorithm; VANET simulator.