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An exponential big bang-big crunch algorithm for discrete design optimization of steel frames

机译:钢框架离散优化设计的指数大爆炸算法

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摘要

In the present study an enhanced variant of the big bang-big crunch (BB-BC) technique, namely exponential BB-BC algorithm (EBB-BC) is developed for code based design optimization of steel frame structures. It is shown that the standard version of the BB-BC algorithm is sometimes unable to produce reasonable solutions to problems from discrete design optimization of steel frames. Hence, through investigating the shortcomings of BB-BC algorithm, it is aimed to reinforce the performance of the technique for this class of problems in particular. The study provides numerical evidences of how the performance of a well-known metaheuristic technique (BB-BC) can significantly be improved through simple yet effective modifications in its formulation to achieve a more robust and reliable variant (EBB-BC). Further, a comparison of the optimum solutions with those of other well-known metaheuristics reveals that the EBB-BC algorithm can efficiently be used as a novel tool for code based design optimization of steel frames.
机译:在本研究中,针对钢框架结构的基于代码的设计优化,开发了大爆炸(BB-BC)技术的增强变体,即指数BB-BC算法(EBB-BC)。结果表明,标准版本的BB-BC算法有时无法为钢框架的离散设计优化产生合理的解决方案。因此,通过研究BB-BC算法的缺点,旨在增强该技术对此类问题的性能。该研究提供了数值证据,说明如何通过对其配方进行简单而有效的修改来显着改善一种著名的元启发式技术(BB-BC)的性能,以实现更强大和可靠的变体(EBB-BC)。此外,将最佳解决方案与其他著名的元启发式方法进行了比较,发现EBB-BC算法可以有效地用作钢框架基于代码的设计优化的新型工具。

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