| 基于ε-支配的自适应多目标进化算法 |
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| 引用本文： | 梁浩,林丹,马楠.基于ε-支配的自适应多目标进化算法[J].计算机工程与应用,2011,47(34):39-43. |
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| 作者姓名： | 梁浩 林丹 马楠 |
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| 作者单位： | 天津大学理学院数学系,天津,300072 |
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| 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。
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| 关 键 词： | 多目标优化 多目标进化算法 ε-支配 ε-自适应调整 |
| 修稿时间： | |
e-dominance based adaptive multi-objective evolutionary algorithm |
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| LIANG Hao,LIN Dan,MA Nan.e-dominance based adaptive multi-objective evolutionary algorithm[J].Computer Engineering and Applications,2011,47(34):39-43. |
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| Authors: | LIANG Hao LIN Dan MA Nan |
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| Affiliation: | LIANG Hao,LIN Dan,MA Nan Department of Mathematics,School of Science,Tianjin University,Tianjin 300072,China |
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| Abstract: | 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. |
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| Keywords: | multi-objective optimization multi-objective evolutionary algorithm ε-dominance ε-adaptive |
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