Design synthesis of microelectromechanical systems using genetic algorithms with component-based genotype representation

被引:0
|
作者
Zhang, Ying [1 ]
Kamalian, Raffi [2 ]
Agogino, Alice M. [3 ]
Sequin, Carlo H. [4 ]
机构
[1] Univ Calif Berkeley, Syst Engn Program, Berkeley, CA 94720 USA
[2] Kyushu Univ, Fac Design, Fukuoka 8158540, Japan
[3] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA
[4] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
关键词
MEMS design synthesis; MOGA; component-based genotype representation; evolutionary multiobjective optimization;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An automated design synthesis system based on a multi-objective genetic algorithm (MOGA) has been developed for the optimization of surface-micromachined MEMS devices. A hierarchical component-based genotype representation is used, which incorporates specific engineering knowledge into the design and optimization process. Each MEMS component is represented by a gene with its own parameters defining its geometry and the way it can be modified from one generation to the next. The object-oriented genotype structures efficiently describe the hierarchical nature typical of engineering designs. They also prevent MOGA from wasting time exploring inappropriate regions of the search space. The automated MEMS design synthesis is demonstrated with surface-micromachined resonator and accelerometer designs. (Track Category: EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION).
引用
收藏
页码:731 / +
页数:2
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