An improved Ant Colony Algorithm based on dynamic weight of pheromone updating

To effectively overcome the defects of local and global pheromone updating for the basic Ant Colony Algorithm, this paper has proposed a new improved Ant Colony Algorithm based on the dynamic adaptive weight in the pheromone updating strategy. The proposed algorithm can update pheromone dynamically and adaptively according to the pheromone density and the quality of iteration-best solutions. By the simulation of several typical Traveling Salesman Problems(TSP), the proposed algorithm is clearly better than several other typically Ant Colony Algorithms in the solution quality and convergence speed. The simulation reflects its effectiveness and feasibility to some extent.