Evolutionary Synthesis of Micromachines Using Supervisory Multiobjective Interactive Evolutionary Computation

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Reference

Raffi R. Kamalian, Ying Zhang, Hideyuki Takagi, and Alice M. Agogino: Evolutionary Synthesis of Micromachines Using Supervisory Multiobjective Interactive Evolutionary Computation. Revised Selected Papers from ICMLC2005, LNAI 3930, Springer-Verlag Berlin Heidelberg, pp.429-437 (2006).

DOI

http://dx.doi.org/10.1007/11739685_45

Abstract

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.

Extended Abstract

Bibtex

Used References

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Kamalian, R., Takagi, H., Agogino, A.M.: The Role of Constraints and Human Interaction in Evolving MEMS Designs: Microresonator Case Study. In: Proceedings of DETC 2004, ASME 2004 Design Engineering Technical Conference, Salt Lake City, UT (2004)

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