TY - GEN
T1 - An approach for multi-objective robust optimization assisted by response surface approximation and visual data-mining
AU - Shimoyama, Koji
AU - Lim, Jin Ne
AU - Jeong, Shinkyu
AU - Obayashi, Shigeru
AU - Koishi, Masataka
PY - 2007/12/1
Y1 - 2007/12/1
N2 - A new approach for multi-objective robust design optimization has been proposed and applied to a real-world design problem with a large number of objective functions. The present approach is assisted by response surface approximation and visual data-mining, which results in two major gains regarding computational time and data interpretation. The Kriging model for response surface approximation can realize accurate predictions of robustness measures, and dramatically reduces the computational time for objective function evaluation. In addition, the use of self-organizing maps as a datamining technique allows visualization of complicated design information between optimality and robustness of design in a comprehensible two-dimensional form. Therefore, the extraction and interpretation of trade-off relations between optimality and robustness of design, and also the location of sweet-spots in the design space, can be performed in a comprehensive manner.
AB - A new approach for multi-objective robust design optimization has been proposed and applied to a real-world design problem with a large number of objective functions. The present approach is assisted by response surface approximation and visual data-mining, which results in two major gains regarding computational time and data interpretation. The Kriging model for response surface approximation can realize accurate predictions of robustness measures, and dramatically reduces the computational time for objective function evaluation. In addition, the use of self-organizing maps as a datamining technique allows visualization of complicated design information between optimality and robustness of design in a comprehensible two-dimensional form. Therefore, the extraction and interpretation of trade-off relations between optimality and robustness of design, and also the location of sweet-spots in the design space, can be performed in a comprehensive manner.
UR - http://www.scopus.com/inward/record.url?scp=79955335832&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79955335832&partnerID=8YFLogxK
U2 - 10.1109/CEC.2007.4424773
DO - 10.1109/CEC.2007.4424773
M3 - Conference contribution
AN - SCOPUS:79955335832
SN - 1424413400
SN - 9781424413409
T3 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
SP - 2413
EP - 2420
BT - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
T2 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
Y2 - 25 September 2007 through 28 September 2007
ER -