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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، 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
آمار
تعداد مشاهده مقاله: 3,951
تعداد دریافت فایل اصل مقاله: 2,969