دوره 9، شماره 4 - ( 6-1398 )                   جلد 9 شماره 4 صفحات 670-651 | برگشت به فهرست نسخه ها

XML English Abstract Print


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

Ghiamat R, Madhkhan M, Bakhshpoori T. OPTIMAL OPERATORS OF GENETIC ALGORITHM IN OPTIMIZING SEGMENTAL PRECAST CONCRETE BRIDGES SUPERSTRUCTURE. International Journal of Optimization in Civil Engineering 2019; 9 (4) :651-670
URL: http://ijoce.iust.ac.ir/article-1-414-fa.html
OPTIMAL OPERATORS OF GENETIC ALGORITHM IN OPTIMIZING SEGMENTAL PRECAST CONCRETE BRIDGES SUPERSTRUCTURE. عنوان نشریه. 1398; 9 (4) :651-670

URL: http://ijoce.iust.ac.ir/article-1-414-fa.html


چکیده:   (13280 مشاهده)
Bridges constitute an expensive segment of construction projects; the optimization of their designs will affect their high cost. Segmental precast concrete bridges are one of the most commonly serviced bridges built for mid and long spans. Genetic algorithm is one of the most widely applied meta-heuristic algorithms due to its ability in optimizing cost. Next to providing cost optimization of these bridge types, the effects of each one of the main three selections, crossover and mutation operators are assessed, and the best operator is determined through the Taguchi experimental design. To validate the functionality of this algorithm, a bridge constructed in the city of Isfahan, Iran (completed in 2017) is optimized, a total of 13% reduction in cost and weight of its superstructure is evident. The efficiency of applying the Taguchi method in determining the type of operators of the genetic algorithm is proved.
متن کامل [PDF 1020 kb]   (3854 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: Optimal design
دریافت: 1398/4/26 | پذیرش: 1398/4/26 | انتشار: 1398/4/26

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 دانشگاه علم و صنعت ایران می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb