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A New Variable Screening Method for Design Optimization of Large-Scale Problems
ISSN: 1946-3979, e-ISSN: 1946-3987
Published April 14, 2015 by SAE International in United States
Citation: Zheng, K., Yang, R., and Hu, J., "A New Variable Screening Method for Design Optimization of Large-Scale Problems," SAE Int. J. Mater. Manf. 8(3):693-696, 2015, https://doi.org/10.4271/2015-01-0478.
Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.