TY - JOUR
T1 - Interactive evolutionary solution synthesis in fuzzy set-based preliminary engineering design
AU - Wang, Jiachuan
AU - Terpenny, Janis
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under Grant No. (DMI-0115211).
PY - 2003/4
Y1 - 2003/4
N2 - This paper describes an interactive evolutionary approach to synthesize component-based preliminary engineering design problems. This approach is intended to address preliminary engineering design as an evolutionary synthesis process, with the needs for human-computer interaction in a changing environment caused by uncertainty and imprecision inherent in the early design stages. It combines an agent-based hierarchical design representation, set-based design generation, fuzzy design trade-off strategy and interactive design adaptation into evolutionary synthesis to gradually refine and reduce the search space while maintaining solution diversity to accommodate future changes. The fitness function of solutions employed is not fixed but adapted according to elicited human value judgment and constraint change. It incorporates multi-criteria evaluation as well as constraint satisfaction. This new approach takes advantage of the different roles of computers and humans play in design and optimization. The methodology will be applicable to general multi-domain applications, with emphasis on physical modeling of dynamic systems. An automotive speedometer design case study is included to demonstrate the methodology.
AB - This paper describes an interactive evolutionary approach to synthesize component-based preliminary engineering design problems. This approach is intended to address preliminary engineering design as an evolutionary synthesis process, with the needs for human-computer interaction in a changing environment caused by uncertainty and imprecision inherent in the early design stages. It combines an agent-based hierarchical design representation, set-based design generation, fuzzy design trade-off strategy and interactive design adaptation into evolutionary synthesis to gradually refine and reduce the search space while maintaining solution diversity to accommodate future changes. The fitness function of solutions employed is not fixed but adapted according to elicited human value judgment and constraint change. It incorporates multi-criteria evaluation as well as constraint satisfaction. This new approach takes advantage of the different roles of computers and humans play in design and optimization. The methodology will be applicable to general multi-domain applications, with emphasis on physical modeling of dynamic systems. An automotive speedometer design case study is included to demonstrate the methodology.
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U2 - 10.1023/A:1022947329200
DO - 10.1023/A:1022947329200
M3 - Article
AN - SCOPUS:0037666034
SN - 0956-5515
VL - 14
SP - 153
EP - 167
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
IS - 2
ER -