An Ant Colony Dynamic Route Guidance Algorithm of Multi-Route Searching Based on Immune Genetics

This paper proposes an algorithm combining the Immune Genetic Algorithm (IGA) with the Ant Colony System Algorithm (ACSA) in order to optimize the travelers' route choices in the process of traffic route guidance. It mainly takes advantage of the dynamism, positive feedback and distributed computing nature of the ACSA, and at the same time compatible with the global searching capability of the IGA and easy to combine with other algorithms. And to improve the evolving speed, this paper proposes a Multi- Route Searching Based on Ant Colony System Algorithm (MRSBACSA). This algorithm is capable of speeding up the convergence, meeting the needs of traffic dynamic changes and satisfying travelers. In the eil51 problem, simulation results indicate that our algorithm worked out a better solution comparing with other algorithms. While simulating real traffic conditions under the MapX environment and looking for an optimal path using our algorithm, simulation results indicate that this proposed algorithm can find a route that meets the travelers' needs in the real road conditions.