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A Hybrid Neural Networks-Coevolution Genetic Algorithm for Multi Variables Robust Design Problem in Quality Engineering | ||
| Journal of Information Technology Management | ||
| مقاله 8، دوره 1، شماره 1، خرداد 2009 اصل مقاله (219.49 K) | ||
| نویسندگان | ||
| mohammad reza mehrgan؛ Ali Reza Farasat* | ||
| چکیده | ||
| In this study, a hybrid algorithm is presented to tackle multi-variables robust design problem. The proposed algorithm comprises neural networks (NNs) and co-evolution genetic algorithm (CGA) in which neural networks are as a function approximation tool used to estimate a map between process variables. Furthermore, in order to make a robust optimization of response variables, co-evolution algorithm is applied to solve constructed model of process. Results of CGA are compared with genetic algorithm (GA). This algorithm is tested in a case study of open-end spinning process. | ||
| کلیدواژهها | ||
| Co evolution Genetic Algorithm؛ Genetic algorithm؛ neural networks؛ Quality Engineering؛ Robust optimization | ||
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آمار تعداد مشاهده مقاله: 3,874 تعداد دریافت فایل اصل مقاله: 2,876 |
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