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Hierarchical component-based representations for evolving microelectromechanical systems designs

Published online by Cambridge University Press:  07 October 2010

Ying Zhang  and
Alice M. Agogino
Ying Zhang
Affiliation:
School of Electrical and Computer Engineering, Georgia Institute of Technology, Savannah, Georgia, USA
Alice M. Agogino
Affiliation:
Department of Mechanical Engineering, University of California, Berkeley, Berkeley, California, USA
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Abstract

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.

Keywords

Component-Based Genotype RepresentationMicroelectromechanical System DesignMultiobjective Genetic Algorithm
Type
Articles
Information
AI EDAM , Volume 25 , Issue 1 , February 2011 , pp. 41 - 55
Copyright
Copyright © Cambridge University Press 2010

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