Evaluating Efficiency of Big-Bang Big-Crunch in Benchmark Engineering Optimization Problems

Date

2011-06-01

Author

Hasançebi, Oğuzhan
Kazemzadeh Azad, Saeid
Erol, Osman Kaan

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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.

Subject Keywords

Engineering optimization, Benchmark problems, Metaheuristics, Big Bang Big Crunch algorithm, Optimum design

URI

https://hdl.handle.net/11511/79204
http://ijoce.iust.ac.ir/article-1-53-en.pdf

Collections

Department of Civil Engineering, Article