A New Multi-objective Differential Evolution Algorithm
Yuelin Gao, Jingke Zhou, Songwei Jia · 2010
A new multi-objective differential evolution algorithm is proposed. A dual elitist selection strategy based on Individual Pareto Rank and Individual Density is employed in the proposed new algorithm. It also remains the characteristic of keeping elitists. The corresponding effects comparisons of new algorithm with other classic multi-objective evolutionary algorithms show that new algorithm require initial population small in size, fewer iterations, and output more optimal solutions. It can improve the diversity metric significantly while ensuring satisfactory convergence metric.