A Study of the Multi-objective Evolutionary Algorithm Based on Elitist Strategy
Chen Wen-bin, Liu YiJun, Wang Li, Liu XiaoLing · 2009
To overcome the decrease of diversity of solutions in NSGA II, a multi-objective evolutionary algorithm based on the elitist strategy, a distribution function is proposed here to improve the elitist strategy. By adjusting the parameters of the distribution function and limiting the elitist solutions, some of the non-elitist solutions will be involved in the genetic computation process. The experimental results show that the improved multi-purpose genetic algorithm has a better diversity and faster convergence of solutions than NSGA II.