Multiple Dynamic Quality Systems Using Hybrid Neuro-Ants Technique

DOI

10.2991/jcis.2006.239How to use a DOI?

Keywords

Artificial network networks, continuous ant colony optimization, dynamic systems, desirability functions, multiple responses, robust design.

Abstract

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.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hsu-Hwa Chang
AU  - Chih-Hsien Chen
AU  - Ching-Shih Tsou
PY  - 2006/10
DA  - 2006/10
TI  - Multiple Dynamic Quality Systems Using Hybrid Neuro-Ants Technique
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SP  - 331
EP  - 334
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.239
DO  - 10.2991/jcis.2006.239
ID  - Chang2006/10
ER  -