Optimized design of MEMS by evolutionary multi-objective optimization with interactive evolutionary computation

Raffi Kamalian, Hideyuki Takagi, Alice M. Agogino

Research output: Contribution to journalArticle

56 Citations (Scopus)

Abstract

We combine interactive evolutionary computation (IEC) with existing evolutionary synthesis software for the design of micromachined resonators and evaluate its effectiveness using human evaluation of the final designs and a test for statistical significance of the improvements. The addition of IEC produces superior designs with fewer potential design or manufacturing problems than those produced through the evolutionary synthesis software alone as it takes advantage of the human ability to perceive design flaws that cannot currently be simulated. A user study has been performed to compare the effectiveness of the IEC enhanced software with the non-interactive software. The results show that the IEC-enhanced synthesis software creates a statistically significant greater number of designs rated best by users.

Original languageEnglish
Pages (from-to)1030-1041
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3103
Publication statusPublished - Dec 1 2004

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Interactive Evolutionary Computation
Micro-Electrical-Mechanical Systems
Evolutionary multiobjective Optimization
Multiobjective optimization
Micro-electro-mechanical Systems
Evolutionary algorithms
MEMS
Software
Synthesis
Software Design
User Studies
Statistical Significance
Resonator
Design
Resonators
Manufacturing
Defects
Evaluate
Evaluation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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