Reduced human fatigue interactive evolutionary computation for micromachine design

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 interactio...

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Bibliographic Details
Published in2005 International Conference on Machine Learning and Cybernetics Vol. 9; pp. 5666 - 5671 Vol. 9
Main Authors Kamalian, Ying Zhang, Takagi, Agogino
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Algorithm design and analysis
CAD
Character generation
Evolutionary computation
Fatigue
Genetic algorithms
Human Interaction
Humans
IEC
Interactive Evolutionary Computation
MEMS
Microelectromechanical systems
Micromachines
Micromechanical devices
MOGA
Testing
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ISBN0780390911
9780780390911
ISSN2160-133X
DOI10.1109/ICMLC.2005.1527946

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Summary: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 n/sup th/-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.
ISBN:0780390911
9780780390911
ISSN:2160-133X
DOI:10.1109/ICMLC.2005.1527946