Hybrid Algorithm Combining Ant Colony Optimization Algorithm with Particle Swarm Optimization

Abstract

By use of the properties of ant colony algorithm and particle swarm optimization, a hybrid algorithm is proposed to solve the traveling salesman problems. First, it adopts statistics method to get several initial better solutions and in accordance with them, gives information pheromone to distribute. Second, it makes use of the ant colony algorithm to get several solutions through information pheromone accumulation and renewal. Finally, by using across and mutation operation of particle swarm optimization, the effective solutions are obtained. Compare with the simulated annealing algorithm, the standard genetic algorithm and the standard ant colony algorithm, all the 16 hybrid algorithms are proved effective. Especially the hybrid algorithm with across strategy B and mutation strategy B is a simple and effective better algorithm than others.