An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation
Kok, Jonathan, Gonzalez, Luis F., Kelson, Neil A., & Periaux, Jacques (2011) An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation. In Poloni, C., Quagliarella, D., Periaux, J., Gauger, N., & Giannakoglou, K. (Eds.) Evolutionary and Deterministic Methods for Design, Optimization and Control (Eurogen 2011), 14-16 September 2011, Italian Aerospace Research Center, Capua.
This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.
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|Item Type:||Conference Paper|
|Keywords:||multi-objective optimisation, multi-disciplinary design optimisation, field programmable gate array|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)|
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation|
Current > QUT Faculties and Divisions > Division of Technology, Information and Learning Support
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Current > Research Centres > High Performance Computing and Research Support
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2011 [please consult the author]|
|Deposited On:||04 Oct 2011 08:37|
|Last Modified:||28 Feb 2013 22:14|
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