Optimization for swarm intelligence based on layer-by-layer evolution

A layer-by-layer evolution strategy was proposed to deal with the premature convergence of swarm intelligence as a collaborator with other existing researches based on pre-experiments and simple proofs. For promoting the precision of solution and eviting the premature convergence, the self-adaption system was constructed on the basis of the primal algorithm, operations such as compression, selection and re-initialization using the technology of layer-by-layer, and the social information was used including the compressed research space and the optimal solution. The improvements of precision of solution and the vitality of terminal individuals can be found in results of simulation experiments with benchmark functions.