Volume 12, Issue 4 (8-2022)                   2022, 12(4): 545-555 | Back to browse issues page

XML Print


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

Sedaghat Shayegan D. OPTIMUM COST DESIGN OF REINFORCED CONCRETE SLABS USING A METAHEURISTIC ALGORITHM. International Journal of Optimization in Civil Engineering 2022; 12 (4) :545-555
URL: http://ijoce.iust.ac.ir/article-1-533-en.html
Abstract:   (434 Views)
In this article, the optimum design of a reinforced concrete solid slab is presented via an efficient hybrid metaheuristic algorithm that is recently developed. This algorithm utilizes the mouth-brooding fish (MBF) algorithm as the main engine and uses the favorable properties of the colliding bodies optimization (CBO) algorithm. The efficiency of this algorithm is compared with mouth-brooding fish (MBF), Neural Dynamic (ND), Cuckoo Search Optimization (COA) and Particle Swarm Optimization (PSO). The cost of the solid slab is considered to be the objective function, and the design is based on the ACI code. The numerical results indicate that this hybrid metaheuristic algorithm can to construct very promising results and has merits in solving challenging optimization problems.
 
Full-Text [PDF 624 kb]   (178 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2022/08/25 | Accepted: 2022/08/19 | Published: 2022/08/19

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2022 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb