Improved multi-objective evolutionary algorithm based on differential evolution

Recently,the use of evolutionary algorithms(EAs) to solve the Multi-objective Optimization Problems(MOPs) has attracted much attention.EA is a population based optimized approach which can find a group of Pareto-optimal solutions in a single run.Differential Evolution(DE) is a branch of EA that is developed to handle problems over continuous domains.An improved Multi-objective Evolutionary Algorithm is proposed based on Differential Evolution(CDE) to solve MOPs.The proposed algorithm is compared to the other two classical Multi-objective Evolutionary algorithms(MOEAs) NSGA-Ⅱ and SPEA2 with the experiment results.