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Evolutionary Algorithms for Planar MEMS Design Optimisation: A Comparative Study

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Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 284))

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Abstract

The evolutionary approach in the design optimisation ofMEMS is a novel and promising research area. The problem is of a multi-objective nature; hence, multi-objective evolutionary algorithms (MOEA) are used. The literature shows that two main classes of MOEA have been used in MEMS evolutionary design Optimisation, NSGA-II and MOGA-II. However, no one has provided a justification for using either NSGA-II or MOGA-II. This paper presents a comparative investigation into the performance of these two MOEA on a number of MEMS design optimisation case studies. MOGA-II proved to be superior to NSGA-II. Experiments are, herein, described and results are discussed.

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Benkhelifa, E., Farnsworth, M., Tiwari, A., Zhu, M. (2010). Evolutionary Algorithms for Planar MEMS Design Optimisation: A Comparative Study. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Studies in Computational Intelligence, vol 284. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12538-6_17

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  • DOI: https://doi.org/10.1007/978-3-642-12538-6_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12537-9

  • Online ISBN: 978-3-642-12538-6

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