Research on Multi-objective Evolutionary Algorithm Based on Island Model
基于岛屿群体模型的多目标演化算法研究

Recently the reaserch on multi-objective evolutionary algorithms based on Pareto optimization concept has become a research hotspot. And it has been widely applied in engineering fields. This paper presented a parallel nondominated sorting genetic multi objective evolutionary algorithm(PNSMEA) based on NSGA-II. PNSMEA adopes island model and the population is divided into several sulrpopulations that evolve separately. The sub-populations migrate good individules each other at intervals of some generations,which can keep individules' diversity and broad the search domain of each sulrpopulation.PNSMEA adopts arithmetic crossover operator to overcome the weak search capability of SBX operator used by NSGA-II.The test results show that PNSMEA can not only improve the premature problem as well as the search capability in the isolated regions of NSGA-II but also contribute to obtaining the Pareto solution sets with better distribution.