摘要
提出一种新的基于ε-支配关系的自适应多目标进化算法(AEMOEA)。在每次的进化中保留端点,并从端点集中选取一个作为父本,参加进化,弥补了ε-MOEA算法中端点易被丢掉的缺陷;在进化过程中根据存档动态地调整ε的取值,使解的分布更加均匀;当存档中个体过多时,运用ε-支配关系进行剪切,使其个体数处在合理水平。通过5个常用双目标测试函数的计算,验证了该算法在求解质量上优于ε-MOEA、NAGA-II以及SPEA-2等主流多目标算法。
A novel multi-objective evolutionary algorithm,called ε -dominance based adaptive multi-objective evolutionary algorithm（AEMOEA）,is proposed.As the improvement to ε -MOEA,the boundary points easily discarded before are reserved in AEMOEA and one of them is chosen as parent to take part in each evolution.In addition,the ε value is dynamically modified with the archive in every generation to find a well-distributed set of solutions.Finally,when the archive is over-sized, ε -dominance is used to reduce it to a proper number.The proposed AEMOEA algorithm is tested on five bi-objective benchmark test functions,and the experimental results demonstrate that AEMOEA outperforms other MOEAs such as ε -MOEA, NAGA-II and SPEA-2.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第34期39-43,共5页
Computer Engineering and Applications
关键词
多目标优化
多目标进化算法
ε-支配
ε-自适应调整
multi-objective optimization
multi-objective evolutionary algorithm
ε-dominance
ε-adaptive
