a1 School of Electrical and Computer Engineering, Georgia Institute of Technology, Savannah, Georgia, USA
a2 Department of Mechanical Engineering, University of California, Berkeley, Berkeley, California, USA
In this paper we present a genotype representation method for improving the performance of genetic-algorithm-based optimal design and synthesis of microelectromechanical systems. The genetic algorithm uses a hierarchical component-based genotype representation, which incorporates specific engineering knowledge into the design optimization process. Each microelectromechanical system 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 encode knowledge-based constraints that prevent the genetic algorithm from wasting time exploring inappropriate regions of the search space. The efficiency of the hierarchical component-based genotype representation is demonstrated with surface-micromachined resonator designs.
(Received July 07 2008)
(Accepted February 11 2010)
(Online publication October 07 2010)
Reprint requests to: Ying Zhang, School of Electrical and Computer Engineering, Georgia Institute of Technology, 210 Technology Circle, Savannah, GA 31407, USA. E-mail: [email protected]