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

26 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
CountryChina
CityGuangzhou
Period8/18/058/21/05

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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