Multiple Dynamic Quality Systems Using Hybrid Neuro-Ants Technique
- Hsu-Hwa Chang 0, Chih-Hsien Chen, Ching-Shih Tsou
- Corresponding Author
- Hsu-Hwa Chang
0National Taipei College of Business
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- https://doi.org/10.2991/jcis.2006.239How to use a DOI?
- Artificial network networks, continuous ant colony optimization, dynamic systems, desirability functions, multiple responses, robust design.
- Robust parameter design has been successfully applied to a variety of engineering problems for enhancing the robustness of the system; however, it cannot deal with multiple dynamic quality systems. Although several other approaches have been presented to resolve this problem, they are unable to efficiently treat the situations that the control factors have continuous values. This study incorporates desirability functions into a hybrid neuro-ants technique to optimize the parameter design of multiple dynamic quality systems with continuous parameters. The objective is to find the best parameter settings so as to maximize simultaneously the robustness of each response. The proposed approach is illustrated with a constructed example.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hsu-Hwa Chang AU - Chih-Hsien Chen AU - Ching-Shih Tsou PY - NaN/NaN DA - NaN/NaN TI - Multiple Dynamic Quality Systems Using Hybrid Neuro-Ants Technique BT - 9th Joint International Conference on Information Sciences (JCIS-06) PB - Atlantis Press UR - https://doi.org/10.2991/jcis.2006.239 DO - https://doi.org/10.2991/jcis.2006.239 ID - ChangNaN/NaN ER -