Volume 1, Issue 3 (9-2011)
2011, 1(3): 495-505 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
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. International Journal of Optimization in Civil Engineering 2011; 1 (3) :495-505
URL: http://ijoce.iust.ac.ir/article-1-53-en.html
URL: http://ijoce.iust.ac.ir/article-1-53-en.html
Abstract: (23553 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.
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
