Multi-Objective Chaotic Evolutionary Algorithm

Multi-objective chaotic evolutionary algorithm(MCEA) is designed.In each generation of MCEA,after the population finishes all genetic operations and external archive maintenance is done,chaotic search is performed on the copy of several individuals randomly chosen from the external archive to obtain new non-dominated solutions.MCEAs respectively merging strength Pareto evolutionary algorithm(SPEA),SPEA2 with chaotic search based on Logistic map are applied to some complex multi-objective optimization problems.The computational results demonstrate that the comprehensive performance of multi-objective evolutionary algorithm(MOEA) is improved as a consequence of the inclusion of chaos.