A many-objective evolutionary algorithm based on rotated grid

A many-objective evolutionary algorithm based on rotated grid
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一种基于旋转网格的多目标进化算法

DOI:
10.1016/j.asoc.2018.02.031
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发表时间:
2018-03
影响因子:
8.7
通讯作者:
Zheng JH
Zheng JH
中科院分区:
计算机科学2区
文献类型:
--
作者:
Zou Juan;Fu Liuwei;Zheng Jinhua;Yang Shengxiang;Yu Guo;Hu Yaru;Zheng Jinhua;Zou Juan;Yang Shengxiang;Yu Guo;Fu LW;Zheng JH

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进化优化算法是一种元启发式方法,在多目标优化问题(MaOP)中经常遇到相当大的挑战。基于帕累托的主导地位在 MaOP 中失去了有效性,MaOP 被定义为具有三个以上的目标。因此,提出了一种更有效的选择方法来平衡收敛和分布。本文提出了一种利用旋转网格技术求解MaOPs的算法(记为RGridEA)。该算法使用旋转网格来划分目标空间。没有使用Pareto非支配排序策略对总体进行分层,而是采用新颖的分层方法来有效增强收敛性,并利用网格来改善分布和均匀性。最后,与其他7种算法一起在DTLZ系列测试函数上进行了测试分析,证实了RGridEA在解决MaOPs方面是有效的。
Evolutionary optimization algorithms, a meta-heuristic approach, often encounter considerable challenges in many-objective optimization problems (MaOPs). The Pareto-based dominance loses its effectiveness in MaOPs, which are defined as having more than three objectives. Therefore, a more valid selection method is proposed to balance convergence and distribution. This paper proposes an algorithm using rotary grid technology to solve MaOPs (denoted by RGridEA). The algorithm uses the rotating grid to partition the objective space. Instead of using the Pareto non-dominated sorting strategy to layer the population a novel stratified method is used to enhance convergence effectively and make use of the grid to improve distribution and uniformity. Finally, with the other seven algorithm was tested on the test function DTLZ series analysis, confirming RGridEA is effective in resolving MaOPs.
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期刊: 2005 IEEE Congress on Evolutionary Computation
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