Study on the Application of Improved Ant Colony Optimization with Particle Swarm Optimization

Ant Colony Algorithms Optimization(ACO) combined with Particle swarm optimization(PSO) integrates each advantage,finds the balance between the local and global best solutions.In every a few generations of ACO,the new algorithm leads the data into PSO in order to accelerate the convergence. The simulation results of eil51 in TSP shows that,compared with the normal ACO,it has amazing efficiency under the appropriate precision and could be widely used