Ant Colony Algorithm Based on Pheromone Declining

Classical ant colony algorithm is found to be deficient for solving Traveling Salesman Problem (TSP) through analyzing ants’ cruising route. Based on these, a new formula updating pheromone was introduced, and ant colony algorithm based on pheromone descending was proposed. The new algorithm avoids the defect that the gradually increased tabu table restricts the selection of ant cruising route during ants looking for the optimized solution, and it reduces the influence of pheromone on subsequent ants, enhances the subsequent ants’ cruising quality. Experimental results on TSP show that the algorithm has faster convergence speed and great stability than that of classical Ant Colony Optimization (ACO) algorithm.