Volume 1, Issue 3 (9-2011)                   IJOCE 2011, 1(3): 495-505 | Back to browse issues page

XML Print


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

Kazemzadeh Azad S, Hasançebi O, Erol O K. EVALUATING EFFICIENCY OF BIG-BANG BIG-CRUNCH ALGORITHM IN BENCHMARK ENGINEERING OPTIMIZATION PROBLEMS. IJOCE 2011; 1 (3) :495-505
URL: http://ijoce.iust.ac.ir/article-1-53-en.html
Abstract:   (25716 Views)
Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers to utilize such techniques in their applications. Big- Bang Big-Crunch (BB-BC) algorithm is a simple metaheuristic optimization method emerged from the Big Bang and Big Crunch theories of the universe evolution. The present study is an attempt to evaluate the efficiency of this algorithm in solving engineering optimization problems. The performance of the algorithm is investigated through various benchmark examples that have different features. The obtained results reveal the efficiency and robustness of the BB-BC algorithm in finding promising solutions for engineering optimization problems.
Full-Text [PDF 209 kb]   (7289 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2012/01/23 | Published: 2011/09/15

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.

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

Designed & Developed by : Yektaweb