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Evaluating Efficiency of Big-Bang Big-Crunch in Benchmark Engineering Optimization Problems
Date
2011-06-01
Author
Hasançebi, Oğuzhan
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
Journal
International Journal of Optimization in Civil Engineering
Collections
Department of Civil Engineering, Article
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O. Hasançebi and O. K. Erol, “Evaluating Efficiency of Big-Bang Big-Crunch in Benchmark Engineering Optimization Problems,”
International Journal of Optimization in Civil Engineering
, pp. 495–505, 2011, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/79204.