Abstract
An efficient and useful robust optimization approach, design for multi-objective six sigma (DFMOSS), has been developed. The DFMOSS couples the ideas of design for six sigma (DFSS) and multi-objective genetic algorithm (MOGA) to solve drawbacks of DFSS; DFMOSS obtains trade-off solutions between optimality and robustness in one optimization. In addition, it does not need careful parameter tuning. Robust optimizations of a test function and welded beam design problem demonstrated that DFMOSS is more effective and more useful than DFSS.
| Original language | English |
|---|---|
| Title of host publication | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings |
| Pages | 950-957 |
| Number of pages | 8 |
| Volume | 1 |
| Publication status | Published - 2005 Oct 31 |
| Externally published | Yes |
| Event | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 - Edinburgh, Scotland, United Kingdom Duration: 2005 Sep 2 → 2005 Sep 5 |
Other
| Other | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 |
|---|---|
| Country/Territory | United Kingdom |
| City | Edinburgh, Scotland |
| Period | 05/9/2 → 05/9/5 |
ASJC Scopus subject areas
- Engineering(all)