Volume 11, Issue 1 (1-2021)                   2021, 11(1): 55-73 | Back to browse issues page

XML Print

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

Sangtarash B H, Ghasemi M R, Ghohani Arab H, Sohrabi M R. HYBRID ARTIFICIAL PHYSICS OPTIMIZATION AND BIG BANG-BIG CRUNCH ALGORITHM (HPBA) FOR SIZE OPTIMIZATION OF TRUSS STRUCTURES. International Journal of Optimization in Civil Engineering. 2021; 11 (1) :55-73
URL: http://ijoce.iust.ac.ir/article-1-465-en.html
Abstract:   (1488 Views)
Over the past decades, several techniques have been employed to improve the applicability of the metaheuristic optimization methods. One of the solutions for improving the capability of metaheuristic methods is the hybrid of algorithms. This study proposes a new optimization algorithm called HPBA which is based on the hybrid of two optimization algorithms; Big Bang-Big Crunch (BB-BC) inspired by the theory of the universe evolution and Artificial Physics Optimization (APO) which is a physical base optimization method. Finally, the performance of the proposed optimization method is compared with the originated methods. Moreover, the performance of the proposed algorithm is evaluated for truss optimization as an applied constrained optimization problem.
Full-Text [PDF 817 kb]   (572 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2021/01/31 | Accepted: 2021/01/1 | Published: 2021/01/1

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

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

© 2021 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb