NDLI: An approach for multi-objective robust optimization assisted by response surface approximation and visual data-mining

Content Provider	IEEE Xplore Digital Library
Author	Shimoyama, K. Jin Ne Lim Shinkyu Jeong Obayashi, S. Koishi, M.
Copyright Year	2007
Description	Author affiliation: Tohoku Univ., Sendai (Shimoyama, K.; Jin Ne Lim; Shinkyu Jeong; Obayashi, S.)
Abstract	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 data-mining 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.
Starting Page	2413
Ending Page	2420
File Size	916586
Page Count	8
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4424773
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Response surface methodology Evolutionary computation Design optimization Genetic mutations Delta modulation
Content Type	Text
Resource Type	Article

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