Multi-objective evolutionary algorithm based on layer strategy

Abstract

In view of the unsatisfactory search performance of binary crossing operator as well as the elitist-preserving approach's influence on the population's diversity, an algorithm of multi-objective based on layer strategy and self-adaptive crossing distribution index is put forward on the basis of research and analysis on NSGA-II algorithm. The algorithm will be applied to the ZDT series test functions. The experiment results show that the improved algorithm maintains the diversity and distribution of population. Compared with NSGA-II, the Pareto front we get is much closer to the true Pareto optimal front. © 2012 Springer-Verlag.