An Improved Ant System Algorithm Based on PPL

To overcome the defect of slow convergence speed, precocity and stagnation in the classical ACO algorithm,the authors propose an Improved Ant System Algorithm Based on PPL to solve TSP according to pheromone updating features of Ant System algorithm, combined with PPL (Parallel Pattern Library) parallel programming idea. The new algorithm combines three different pheromone update methods to make a new pheromone decreasing update method. It effectively reduces the influence of pheromone on the non-optimal path during ants looking for the optimized solution to subsequent ants and improves the cruising quality of subsequent ants. It makes full use of multi-core CPU´s computing power and improves the efficiency significantly. Experimental results on TSP show that The new algorithm presented in this paper has a better global searching ability, higher convergence speed and solution diversity than that of classical ACO algorithm.