Evolutionary Synthesis of Micromachines Using Supervisory Multiobjective Interactive Evolutionary Computation

  • Raffi Kamalian
  • Ying Zhang
  • Hideyuki Takagi
  • Alice M. Agogino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


A novel method of Interactive Evolutionary Computation (IEC) for the design of microelectromechanical systems (MEMS) is presented. As the main limitation of IEC is human fatigue, an alternate implementation that requires a reduced amount of human interaction is proposed. The method is applied to a multi-objective genetic algorithm, with the human in a supervisory role, providing evaluation only every n th -generation. Human interaction is applied to the evolution process by means of Pareto-rank shifting for the fitness calculation used in selection. The results of a test on 13 users shows that this IEC method can produce statistically significant better MEMS resonators than fully automated non-interactive evolutionary approaches.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Raffi Kamalian
    • 1
  • Ying Zhang
    • 2
  • Hideyuki Takagi
    • 1
  • Alice M. Agogino
    • 2
  1. 1.Faculty of DesignKyushu UniversityFukuokaJapan
  2. 2.BEST LabUniversity of CaliforniaBerkeleyUSA

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