title: |
Multiple Dynamic Quality Systems Using Hybrid Neuro-Ants Technique |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-01-7 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/jcis.2006.239 (how to use a DOI) | |
author(s): |
Hsu-Hwa Chang, Chih-Hsien Chen, Ching-Shih Tsou |
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corresponding author: |
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publication date: |
October 2006 |
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keywords: |
Artificial network networks, continuous ant colony optimization, dynamic systems, desirability functions, multiple responses, robust design. |
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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. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |