جلد 22، شماره 3 - ( 9-1390 )                   جلد 22 شماره 3 صفحات 233-225 | برگشت به فهرست نسخه ها

XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Amin-Naseri M, Baradaran Kazemzadeh R, Salmasnia A, Salehi M. Optimizing Multiple Response Problem Using Artificial Neural Networks and Genetic Algorithm. Journal title 2011; 22 (3) :225-233
URL: http://ijiepm.iust.ac.ir/article-1-730-fa.html
Optimizing Multiple Response Problem Using Artificial Neural Networks and Genetic Algorithm. عنوان نشریه. 1390; 22 (3) :225-233

URL: http://ijiepm.iust.ac.ir/article-1-730-fa.html


چکیده:   (5460 مشاهده)

  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 .

متن کامل [PDF 265 kb]   (1769 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: سایر موضوعاتی که به مرزهای دانش در مهندسی صنایع و تولید کمک می کند
دریافت: 1390/9/20 | پذیرش: 1392/4/24 | انتشار: 1392/4/24

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به نشریه بین المللی مهندسی صنایع و مدیریت تولید می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق