Structural Topology Optimization of Magnetic Actuators Using Genetic Algorithms and ON/OFF Sensitivity
Structural Topology Optimization of Magnetic Actuators Using Genetic Algorithms and ON/OFF Sensitivity
复制标题
使用遗传算法和开/关灵敏度优化磁致动器的结构拓扑
DOI：
10.1109/tmag.2009.2016297
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发表时间：
2009
影响因子：
2.1
通讯作者：
J. Yoo
中科院分区：
文献类型：
--
作者：
J. Choi;J. Yoo
在基于遗传算法（GA）的拓扑优化问题中，初始种群的特性对快速稳定的收敛有重要影响。本文介绍了一种随机产生具有上级遗传特性的初始种群的算法。为了避免小结构点的产生，提出了模糊技术。重点研究了在设计域中控制磁通量流动的种子单元的连通性。在传统的线性串遗传算法的基础上，引入了二维染色体和地理交叉方法，以增加后代的多样性。将所提出的设计算法应用于磁致动器的磁轭优化。
In genetic algorithm (GA) based topology optimization problems, characteristics of an initial population are important for the rapid and stable convergence. This paper introduces an algorithm generating randomly an initial population with superior hereditary characteristics. To avoid the generation of small structural spots, the blurring technique is proposed. The connectivity of seed elements considerging the magnetic flux flow in the design domain is focused. Differently from the classical GA by linear strings, this study deals with two-dimensonal chromosomes and the geographic crossover method to increase the diversity of offspring. The proposed design algorithm is applied to the yoke optimization of magnetic actuators.