A new efficient and useful robust optimization approach - design for multi-objective six sigma

by: K Shimoyama, A Oyama, K Fujii

Evolutionary Computation, 2005. The 2005 IEEE Congress on, Vol. 1 (2005), pp. 950-957 Vol.1.

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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.

@inproceedings{shimoyama05, 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.}, author = {Shimoyama, K. and Oyama, A. and Fujii, K. }, booktitle = {Evolutionary Computation, 2005. The 2005 IEEE Congress on}, citeulike-article-id = {2813291}, doi = {http://dx.doi.org/10.1109/CEC.2005.1554785}, journal = {Evolutionary Computation, 2005. The 2005 IEEE Congress on}, keywords = {multiobjectifs, optimisation, robuste}, pages = {950--957 Vol.1}, posted-at = {2008-05-20 14:48:17}, priority = {0}, title = {A new efficient and useful robust optimization approach - design for multi-objective six sigma}, url = {http://dx.doi.org/10.1109/CEC.2005.1554785}, volume = {1}, year = {2005} }

RIS record

TY - CONF ID - shimoyama05 L3 - citeulike-article-id:2813291 TI - A new efficient and useful robust optimization approach - design for multi-objective six sigma T2 - Evolutionary Computation, 2005. The 2005 IEEE Congress on JF - Evolutionary Computation, 2005. The 2005 IEEE Congress on VL - 1 SP - 950 EP - 957 Vol.1 N2 - 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. KW - multiobjectifs KW - optimisation KW - robuste AU - Shimoyama, K AU - Oyama, A AU - Fujii, K PY - 2005/// UR - http://dx.doi.org/10.1109/CEC.2005.1554785 ER -

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