Univrsity Of Tehran Press Journal of Information Technology Management 2980-7972 1 1 2009 02 19 A Hybrid Neural Networks-Coevolution Genetic Algorithm for Multi Variables Robust Design Problem in Quality Engineering ارائه یک الگوریتم ترکیبی شبکه‌های عصبی- تکامل توام ژنتیک، جهت مساله طراحی مقاوم چند متغیره در مهندسی کیفیت 27732 EN Mohammad Reza Mehrgan 0000-0002-7974-8171 Ali Reza Farasat Journal Article 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. Co evolution Genetic Algorithm Genetic algorithm neural networks Quality Engineering Robust optimization https://jitm.ut.ac.ir/article_27732_123f06c5f8bcd6e2bd7cae3eefae4abb.pdf