Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (25): 49-53.

• 研究、探讨 • Previous Articles     Next Articles

Improved multi-objective evolutionary algorithm based on adaptive neighborhood

XUE Shengjun,YANG Ming   

  1. Institute of Computer and Software,Nanjing University of Information Science and Technology,Nanjing 210044,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-09-01 Published:2011-09-01

改进的自适应邻域的多目标进化算法

薛胜军,杨 明   

  1. 南京信息工程大学 计算机与软件学院,南京 210044

Abstract: A novel Multi-Objective Evolutionary Algorithm based on Adaptive Neighborhood(ANMOEA) is proposed.In the ANMOEA,an adaptive neighborhood method is used to maintain the diversity of the population.Moreover,this paper discusses that the radius of the neighborhood is adaptively changed by the situation of the current population,which avoids the problem that radius value of the neighborhood affects the diversity of the population in the traditional neighborhood strategy.In addition,adaptive neighborhood radius and crowding distance are applied to evaluate density of individuals,which preserves the small density of the individuals.The experimental results indicate that the discussed method is effective in maintaining the diversity of the population,which is significantly stronger than NSGAII and NMOEA multi-objective algorithm.

Key words: adaptive neighborhood radius, multi-objective optimization, neighborhood set, adaptive neighborhood

摘要: 提出了一种新的自适应邻域的多目标进化算法,该算法采用自适应邻域的方法维护群体的分布性。探讨了根据当前群体情况进行自适应改变邻域半径,避免了传统邻域策略所引起的邻域半径的取值影响群体分布性的问题。另外,利用自适应邻域半径和拥挤距离进行密度估计,使密度小的个体得到保留。实验结果表明,所讨论的方法是有效的,在保持群体分布性上优于NSGAII和NMOEA。

关键词: 自适应邻域半径, 多目标进化算法, 邻域集, 自适应邻域