Six Sigma Quality Approach to Robust Optimization

In electromagnetic design, uncertainties in design variables are inevitable, thus in addition to pursuing the theoretical optimum of the objective function the evaluation of robustness of the optimum solution is also critical. Several methodologies exist to tackle robust optimization, such as worst...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2015-03, Vol.51 (3), p.1-4
Main Authors: Song Xiao, Yinjiang Li, Rotaru, Mihai, Sykulski, Jan K.
Format: Article
Language:English
Subjects:
Balancing
Benchmarking
Electromagnetics
Exploitation
Exploration
Linear programming
Magnetism
Mathematical models
Optimization
Robustness
Six sigma
Standard deviation
Uncertainty
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Summary:In electromagnetic design, uncertainties in design variables are inevitable, thus in addition to pursuing the theoretical optimum of the objective function the evaluation of robustness of the optimum solution is also critical. Several methodologies exist to tackle robust optimization, such as worst case optimization and gradient index; this paper investigates the use of standard deviation and mean value of objective function under uncertainty of variables. A modified Kriging model with the ability of balancing exploration and exploitation is employed to facilitate the objective function prediction. Two TEAM benchmark problems are solved using different methodologies to compare the advantages and disadvantages of different robust optimization approaches.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2014.2360435