电子学报 ›› 2020, Vol. 48 ›› Issue (8): 1596-1604.DOI: 10.3969/j.issn.0372-2112.2020.08.019
孙文静, 李军华, 黎明
收稿日期:
2019-11-16
修回日期:
2020-01-10
出版日期:
2020-08-25
发布日期:
2020-08-25
通讯作者:
李军华
作者简介:
孙文静 女,汉族,1995年生于安徽广德,现为南昌航空大学硕士研究生,主要研究方向为进化算法. E-mail:18970941060@163.com
基金资助:
SUN Wen-jing, LI Jun-hua, LI Ming
Received:
2019-11-16
Revised:
2020-01-10
Online:
2020-08-25
Published:
2020-08-25
摘要: 基于松弛支配的高维多目标进化算法(Many-objective Evolutionary Algorithms,MaOEAs)由于能够有效地提高区分解的能力,受到广泛关注,但该类大多数算法处理不同目标的优化问题时普适性较差.针对这个问题,本文提出一种基于自适应支配准则的高维多目标进化算法(Adaptive Dominance Criterion Based Evolutionary Algorithm for Many-objective Optimization,ADCEA).首先,自适应准则(Adaptive Dominance Criterion,ADC)根据目标空间中相邻解间的角度信息和目标数目,设计一种自适应小生境方法,并结合收敛性指标信息,实现对候选解的非支配排序.然后,为了进一步增强种群的多样性,在环境选择中引入参考向量分割种群技术;最后,构建合理的适应度函数,并根据适应度值大小选取收敛性和多样性较好的非支配解集.实验证明,本文所提的方法在处理不同目标的优化问题时普适性提高,并在平衡种群的收敛性和多样性上取得显著效果.
中图分类号:
孙文静, 李军华, 黎明. 基于自适应支配准则的高维多目标进化算法[J]. 电子学报, 2020, 48(8): 1596-1604.
SUN Wen-jing, LI Jun-hua, LI Ming. Adaptive Dominance Criterion Based Evolutionary Algorithm for Many-objective Optimization[J]. Acta Electronica Sinica, 2020, 48(8): 1596-1604.
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