An Ant System with Two Colonies and Its Application to Traveling Salesman Problem

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An ant system with two colonies is proposed for the combinatorial optimization problems. The proposed method is inspired by the knowledge that there are many colonies of ants in the natural world. The proposed two-colony mechanism plays an important role in enhancing the diversification while maintaining the intensification of the algorithm. At first, ants perform solution search procedure by cooperating with each others in the same colony until no better solution is found after a certain time period. Then, communication between the two colonies is performed to build new pheromone distributions for each colony, and ants start their search procedure again in each separate colony, based on the new pheromone distribution. Furthermore, in order to enhance the quality of the iteratively found solutions, a local search algorithm is also adopted. The proposed algorithm is tested by simulating the Traveling Salesman Problem (TSP). Simulation results show that the proposed method performs better than the traditional ACO algorithms.

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