A mutation hybrid algorithm of particle swarm optimization

Many mutation functions of particle positions are discussed in this paper. It is discussed the global searching capability, the local searching capability and the traversal capability of these mutation functions. And a mutation hybrid algorithm of particle swarm optimization is brought out in this paper. In each iteration, the position of particles which is satisfied the mutation condition are mutated with many kind of mutation functions, and each mutation function is endowed a probability. The probability distribution is relied on the specific optimization problem. Some experiments results of standard PSO, single mutation PSO and multi-mutation PSO are contrasted. It indicates that if the probability distribution of mutation functions set is well formed, the multi-mutation PSO will search the global best value more quickly and effectively.