A Multi-swarm Co-evolutionparticle Swarm Optimization Algorithm Combined with the Extremal Optimization Algorithm

The multi-swarm co-evolution particle swarm optimization algorithm is an algorithm based on swarm intelligence,with intelligence,versatility,parallelism and global searching ability,can solve the problem of global optimization very well,however, mechanism to keep the diversity of particles and co-evolution mechanism need to be further improved. In order to further improve the optimization efficiency of the muti-swarm co-evolution particle swarm optimization algorithm,we propose a new muti-swarm co-evolution particle swarm optimization algorithm combined with the extreme optimization algorithm(MCPSOEO), combine the global searching ability of the multi-swarm co-evolution particle swarm optimization algorithm and the local searching ability of the extreme optimization.Finally,the experimental results prove the effectiveness of the algorithm.