دوره 12، شماره 3 - ( 2-1401 )                   جلد 12 شماره 3 صفحات 312-279 | برگشت به فهرست نسخه ها

XML English Abstract Print


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

Biabani F, Razzazi A, Shojaee S, Hamzehei-Javaran S. DESIGN AND APPLICATION OF A HYBRID META-HEURISTIC OPTIMIZATION ALGORITHM BASED ON THE COMBINATION OF PSO, GSA, GWO AND CELLULAR AUTOMATION. International Journal of Optimization in Civil Engineering 2022; 12 (3) :279-312
URL: http://ijoce.iust.ac.ir/article-1-520-fa.html
DESIGN AND APPLICATION OF A HYBRID META-HEURISTIC OPTIMIZATION ALGORITHM BASED ON THE COMBINATION OF PSO, GSA, GWO AND CELLULAR AUTOMATION. عنوان نشریه. 1401; 12 (3) :279-312

URL: http://ijoce.iust.ac.ir/article-1-520-fa.html


چکیده:   (5038 مشاهده)
Presently, the introduction of intelligent models to optimize structural problems has become an important issue in civil engineering and almost all other fields of engineering. Optimization models in artificial intelligence have enabled us to provide powerful and practical solutions to structural optimization problems. In this study, a novel method for optimizing structures as well as solving structure-related problems is presented. The main purpose of this paper is to present an algorithm that addresses the major drawbacks of commonly-used algorithms including the Grey Wolf Optimization Algorithm (GWO), the Gravitational Search Algorithm (GSA), and the Particle Swarm Optimization Algorithm (PSO), and at the same time benefits from a high convergence rate. Also, another advantage of the proposed CGPGC algorithm is its considerable flexibility to solve a variety of optimization problems. To this end, we were inspired by the GSA law of gravity, the GWO's top three search factors, the PSO algorithm in calculating speed, and the cellular machine theory in the realm of population segmentation. The use of cellular neighborhood reduces the likelihood of getting caught in the local optimal trap and increases the rate of convergence to the global optimal point. Achieving reasonable results in mathematical functions (CEC 2005) and spatial structures (with a large number of variables) in comparison with those from GWO, GSA, PSO, and some other common heuristic algorithms shows an enhancement in the performance of the introduced method compared to the other ones.
 
متن کامل [PDF 1144 kb]   (2063 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: Optimal design
دریافت: 1401/1/28 | پذیرش: 1401/1/14 | انتشار: 1401/1/14

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