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In this paper we propose an optimal routing method for cars in car navigation system. The proposed method finds the paths with a combination of Divide and Conquer method and Ant Colony algorithm. In order to do this, the road network is divided to small areas. Then the learning operation is done in these small areas. Then different learnt paths are combined together to make the complete paths. This method causes balance and reduces the traffic in lanes of the pathes, because it not only consider lengths of the paths for learning operations, it also considers the other factor which is traffic condition of the lanes of the paths. Consequently this method reduces the average triptime of the cars in comparison with existing Ant Colony, Genetic and Dijkstra algorithms by reducing and balancing of road traffic. Therefore, some improvements in the average traveling time of vehicles are achieved. Also, this results in short and precise paths and learning stage becomes faster

international journal of machine learning and computing

The Optimal Routing of Cars in the Car Navigation System by Taking the Combination of Divide and Conquer Method and Ant Colony Algorithm into Consideration