Optimized Design of MEMS by Evolutionary Multi-objective Optimization with Interactive Evolutionary Computation
Inhaltsverzeichnis
Reference
Raffi Kamalian, Hideyuki Takagi, and Alice M. Agogino: Optimized Design of MEMS by Evolutionary Multi-objective Optimization with Interactive Evolutionary Computation. Genetic and Evolutionary Computation (GECCO2004), Seattle, WA, pp. 1030-1041 (June 26-30, 2004).
DOI
http://link.springer.com/chapter/10.1007%2F978-3-540-24855-2_114
Abstract
We combine interactive evolutionary computation (IEC) with existing evolutionary synthesis software for the design of micromachined resonators and evaluate its effectiveness using human evaluation of the final designs and a test for statistical significance of the improvements. The addition of IEC produces superior designs with fewer potential design or manufacturing problems than those produced through the evolutionary synthesis software alone as it takes advantage of the human ability to perceive design flaws that cannot currently be simulated. A user study has been performed to compare the effectiveness of the IEC enhanced software with the non-interactive software. The results show that the IEC-enhanced synthesis software creates a statistically significant greater number of designs rated best by users.
Extended Abstract
Bibtex
Used References
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Links
Full Text
http://best.berkeley.edu/~raffi/papers/GECCO2004_31031030.pdf
