Abstract
This paper examines optimization techniques for parametric design based on statistical, mathematical, and heuristic models. A hybrid method is then proposed based on the strengths of several of these approaches. The new method, called multi-target parametric design method, combines Taguchi, methodology, conventional (mathematical) optimization methods, and MANOVA statistical technique. It can be used to optimize composite utility functions, while satisfying the quality requirements. The method involves three main steps. First by applying Taguchi's method, the optimal quality is determined with a certain set of control variables. Second, these variables are transformed into variable constraints through a relaxing process. Finally, the optimization problem is solved for other design targets under these constraints, using conventional mathematical optimization methods or the Taguchi method.
| Original language | English (US) |
|---|---|
| Title of host publication | American Society of Mechanical Engineers, Design Engineering Division (Publication) DE |
| Editors | Mo Shahinpoor, H.S. Tzou |
| Place of Publication | New York, NY, United States |
| Publisher | Publ by ASME |
| Pages | 599-566 |
| Number of pages | 34 |
| Volume | 65 pt 1 |
| ISBN (Print) | 0791811816 |
| State | Published - 1993 |
| Event | 14th Biennial Conference on Mechanical Vibration and Noise - Albuquerque, NM, USA Duration: Sep 19 1993 → Sep 22 1993 |
Other
| Other | 14th Biennial Conference on Mechanical Vibration and Noise |
|---|---|
| City | Albuquerque, NM, USA |
| Period | 9/19/93 → 9/22/93 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Hybrid method for multi-target parametric design. / Shah, Jami J.; Wu, Jian.
American Society of Mechanical Engineers, Design Engineering Division (Publication) DE. ed. / Mo Shahinpoor; H.S. Tzou. Vol. 65 pt 1 New York, NY, United States : Publ by ASME, 1993. p. 599-566.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Hybrid method for multi-target parametric design
AU - Shah, Jami J.
AU - Wu, Jian
PY - 1993
Y1 - 1993
N2 - This paper examines optimization techniques for parametric design based on statistical, mathematical, and heuristic models. A hybrid method is then proposed based on the strengths of several of these approaches. The new method, called multi-target parametric design method, combines Taguchi, methodology, conventional (mathematical) optimization methods, and MANOVA statistical technique. It can be used to optimize composite utility functions, while satisfying the quality requirements. The method involves three main steps. First by applying Taguchi's method, the optimal quality is determined with a certain set of control variables. Second, these variables are transformed into variable constraints through a relaxing process. Finally, the optimization problem is solved for other design targets under these constraints, using conventional mathematical optimization methods or the Taguchi method.
AB - This paper examines optimization techniques for parametric design based on statistical, mathematical, and heuristic models. A hybrid method is then proposed based on the strengths of several of these approaches. The new method, called multi-target parametric design method, combines Taguchi, methodology, conventional (mathematical) optimization methods, and MANOVA statistical technique. It can be used to optimize composite utility functions, while satisfying the quality requirements. The method involves three main steps. First by applying Taguchi's method, the optimal quality is determined with a certain set of control variables. Second, these variables are transformed into variable constraints through a relaxing process. Finally, the optimization problem is solved for other design targets under these constraints, using conventional mathematical optimization methods or the Taguchi method.
UR - http://www.scopus.com/inward/record.url?scp=0027833107&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0027833107&partnerID=8YFLogxK
M3 - Conference contribution
SN - 0791811816
VL - 65 pt 1
SP - 599
EP - 566
BT - American Society of Mechanical Engineers, Design Engineering Division (Publication) DE
A2 - Shahinpoor, Mo
A2 - Tzou, H.S.
PB - Publ by ASME
CY - New York, NY, United States
ER -