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Ant colony algorithm based on pheromone intensity
基于信息素强度的蚁群算法

Keywords: Ant Colony Optimization (ACO),intensity of pheromone,dynamic pheromone updating,Traveling Salesman Problem (TSP)
蚁群算法
,信息素强度,动态信息素更新,旅行商问题

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Abstract:

When selecting the path, all the existing ant colony algorithms take account of the information of pheromone and distance. In order to simulate the real ant better, this paper proposed a new ant colony algorithm based on the intensity of pheromone, which only depended on the intensity of pheromone when selecting the path. The path length (or distance) was used when initializing and updating the pheromone. A strategy of dynamic pheromone update was given. The experiments demonstrate that the proposed algorithm can obtain good searching results, and the speed of operation is more than five times faster than the existing ant colony algorithms.

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