W. Ngenkaew, S. Ono, and S. Nakayama (Japan)
Ant-Based Clustering, Pheromone Influence, Data Cluster ing, Ant Foraging, and Multiple Pheromones
This paper focuses on Ant-Based Clustering algorithm from an ant foraging model’s view, and proposes a method of using two kinds of deposited pheromones at each grid, Trailing Pheromone and Foraging Pheromone. The ex perimental results show that the use of two kinds of pheromones improves foraging time efficiency for ants compared with the basic algorithm without any pheromone and with only Trailing Pheromone.
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