Reduced human fatigue interactive evolutionary computation for micromachine design

Raffi Kamalian, Ying Zhang, Hideyuki Takagi, Alice M. Agogino

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    28 Citations (Scopus)

    Abstract

    This paper presents a novel method of using Interactive Evolutionary Computation (IEC) for the design of Microelectromechanical Systems (MEMS). A key limitation of IEC is human fatigue. Based on the results of a study of a previous IEC MEMS tool, an alternate form that requires less human interaction is presented. The method is applied on top of a conventional multi-objective genetic algorithm, with the human in a supervisory role, providing evaluation only every nth-generation. Human interaction is applied to the evolution process by means of Pareto-rank shifting, which is used for the fitness calculation used in selection. Results of a test of 13 users shows that this IEC method can produce statistically significant better MEMS resonators than non-interactive evolutionary synthesis.

    Original languageEnglish
    Title of host publication2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
    PublisherIEEE Computer Society
    Pages5666-5671
    Number of pages6
    ISBN (Print)078039092X, 9780780390928
    DOIs
    Publication statusPublished - 2005
    EventInternational Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China
    Duration: Aug 18 2005Aug 21 2005

    Publication series

    Name2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

    Other

    OtherInternational Conference on Machine Learning and Cybernetics, ICMLC 2005
    Country/TerritoryChina
    CityGuangzhou
    Period8/18/058/21/05

    All Science Journal Classification (ASJC) codes

    • General Engineering

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