电子学报2016，Vol.44Issue(5)：1071-1077,7.DOI:10.3969/j.issn.0372-2112.2016.05.009
一种改进的基于密度的多目标进化算法
An Improved Density-Driven Multi-objective Evolutionary Algotithm
摘要
Abstract
Multi-objective evolutionary algorithm that diversifies population by its density (MODdEA)solve multi-objective optimization problem according to the non-dominated sorting information and spatial density information,the algo-rithm has a good performance in the comparison with other multi-objective evolutionary algorithm.In this paper,we propose an improved multi-objective evolutionary algorithm MODdEA +based on MODdEA.Firstly,we propose a operator named clone operator based on the partition mechanism in search space,this operator could not only improve the global search capa-bilities in the early stage of evolution,but also enhance the local refinement capabilities in the late stage of evolution;second-ly,we introduce a evaluation strategy which evaluate the individuals in Pareto information list based on the dominate and dominated information,this strategy provide a more accurate sorting result;finally,we improve the mutation operator in order to reduce the probability of overstep of the boundary.To demonstrate the effectiveness of the improved algorithm,we com-pare it with MODdEA on multiple testing problems,the experimental results show that the improved algorithm’s solving quality is much better than the original algorithm’s.关键词
进化算法/密度驱动/克隆操作/粗适应度值/变异操作Key words
evolutionary algorithm/density-driven/clone operator/raw fitness/mutation operator分类
信息技术与安全科学引用本文复制引用
王鹏,张长胜,张斌,刘婷婷..一种改进的基于密度的多目标进化算法[J].电子学报,2016,44(5):1071-1077,7.基金项目
宁夏回族自治区自然科学基金（No．NZ13265）；中央高校东北大学基本科研专项基金 （）
