fa سایر موضوعاتی که به مرزهای دانش در مهندسی صنایع و تولید کمک می کند Other related Industrial and production reserach subjects in which has direct relation to the state-of-the art of the IE پژوهشي Research <p> <i> This paper proposes a new intelligent approach for solving multi-response statistical optimization problems. In most real world optimization problems, we are encountered adjusting process variables to achieve optimal levels of output variables (response variables). Usual optimization methods often begin with estimating the relation function between the response variable and the control variables. Among these techniques, the response surface methodology (RSM) due to its simplicity has attracted the most attention in recent years. However, in some cases the relationship between the response variable and the control factors is so complex hence a good estimate of the response variable cannot be achieved using polynomial regression models. An alternative approach presented in this study employs artificial neural networks to estimate response functions and genetic algorithm to optimize the process. Furthermore, the proposed approach uses taguchi robust parameter design to overcome the common limitation of the existing multi-response approaches, which typically ignore the dispersion effect of the responses. In order to evaluate the effectiveness of the proposed method, the method has been applied to a numerical example from litterateur and the results were satisfactory </i><i>. </i></p> Multiple Response Optimization, Taguchi method, Artificial neural network, Genetic algorithm 225 233 http://ijiepm.iust.ac.ir/browse.php?a_code=A-10-128-5&slc_lang=fa&sid=1 M.R. Amin-Naseri amin_nas@modares.ac.ir 180031947532846005290 180031947532846005290 Yes Faculty of Industrial Engineering, Tarbiat Modares University R., Baradaran Kazemzadeh 180031947532846005291 180031947532846005291 No Faculty of Industrial Engineering, Tarbiat Modares University, A. Salmasnia 180031947532846005292 180031947532846005292 No Faculty of Industrial Engineering, Tarbiat Modares University, M. Salehi 180031947532846005293 180031947532846005293 No Faculty of Industrial Engineering, Tarbiat Modares University