Abstract
An interactive hybrid evolutionary computation (IHC) process for MEMS design synthesis is described, which uses both human expertise and local performance improvement to augment the performance of an evolutionary process. The human expertise identifies good design patterns, and local optimization fine-tunes these designs so that they reach their potential at early stages of the evolutionary process. At the same time, the feedback on local optimal designs confirms and refines the human assessment. The advantages of the IHC process are demonstrated with micromachined resonator test cases.
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Zhang, Y., Agogino, A.M. (2010). Interactive Hybrid Evolutionary Computation for MEMS Design Synthesis. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_24
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DOI: https://doi.org/10.1007/978-3-642-12990-2_24
Publisher Name: Springer, Berlin, Heidelberg
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