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An efficient evolutionary multi-objective framework for MEMS design optimisation: validation, comparison and analysis

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Abstract

The application of multi objective evolutionary algorithms (MOEA) in the design optimisation of microelectromechanical systems (MEMS) is of particular interest in this research. MOEA is a class of soft computing techniques of biologically inspired stochastic algorithms, which have proved to outperform their conventional counterparts in many design optimisation tasks. MEMS designers can utilise a variety of multi-disciplinary design tools that explore a complex design search space, however, still follow the traditional trial and error approaches. The paper proposes a novel framework, which couples both modelling and analysis tools to the most referenced MOEAs (NSGA-II and MOGA-II). The framework is validated and evaluated through a number of case studies of increasing complexity. The research presented in this paper unprecedentedly attempts to compare the performances of the mentioned algorithms in the application domain. The comparative study shows significant insights into the behaviour of both of the algorithms in the design optimisation of MEMS. The paper provides extended discussions and analysis of the results showing, overall, that MOGA-II outperforms NSGA-II, for the selected case studies.

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Authors and Affiliations

  1. Decision Engineering Centre, Cranfield University, College Road, Bedfordshire, MK43 0AL, UK

    Michael Farnsworth & Ashutosh Tiwari

  2. Mobile Fusion Applied Research Centre, Staffordshire University, Stafford, Staffordshire, ST18 0AD, UK

    Elhadj Benkhelifa & Mansour Moniri

  3. Microsystems and Nanotechnology Centre, Cranfield University, College Road, Bedfordshire, MK43 0AL, UK

    Meiling Zhu

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  1. Michael Farnsworth
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  3. Ashutosh Tiwari
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  4. Meiling Zhu
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  5. Mansour Moniri
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Correspondence to Michael Farnsworth.

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Farnsworth, M., Benkhelifa, E., Tiwari, A. et al. An efficient evolutionary multi-objective framework for MEMS design optimisation: validation, comparison and analysis. Memetic Comp. 3, 175–197 (2011). https://doi.org/10.1007/s12293-011-0067-6

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