Evolutionary Algorithms for Planar MEMS Design Optimisation: A Comparative Study

• Elhadj Benkhelifa ^[1] ; Michael Farnsworth ^[1] ; Ashutosh Tiwari ^[1] ; Meiling Zhu ^[1]
  1. [1] Universidad de Cranfield
• Localización: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) / coord. por Juan R. González, David Alejandro Pelta Mochcovsky, Carlos Cruz, Germán Terrazas, Natalio Krasnogor, 2010, ISBN 978-3-642-12537-9, págs. 199-210
• Idioma: inglés
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• Resumen

  • The evolutionary approach in the design optimisation of MEMS 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.