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Truss-sizing optimization attempts with CSA: a detailed evaluation
Soft Computing ( IF 4.1 ) Pub Date : 2020-05-02 , DOI: 10.1007/s00500-020-04972-y
Hakan Ozbasaran , Meltem Eryilmaz Yildirim

Thanks to the advent of powerful computers, searching for optimal solutions to engineering design problems becomes easier every day. Numerous researchers are still developing modern optimization algorithms, and the competition for “the most efficient optimization algorithm” continues apace. This study evaluates the performances of the Crow Search Algorithm (CSA) and a slightly modified variant (CSAM) in one of the most popular and controversial competitions in the structural optimization field for the first time. Unlike most of the works on structural optimization, this paper does not tell a success story. After days of computation to collect the sensitivity and convergence data, it is shown that both CSA and CSAM mostly fail compared to today’s competitive algorithms. The findings of the study are discussed through tables and plots in detail to share the unfavorable experience on the truss optimization attempts, to review the difficulties of using parameter-controlled algorithms in structural optimization through CSA, and to save time for the researchers in the field.



中文翻译:

使用CSA进行桁架尺寸优化尝试:详细评估

得益于功能强大的计算机的出现,每天都更容易找到针对工程设计问题的最佳解决方案。许多研究人员仍在开发现代优化算法,“最有效的优化算法”的竞争仍在继续。这项研究首次评估了Crow Search算法(CSA)和略微修改的变体(CSA M)在结构优化领域最流行和有争议的竞赛之一中的性能。与大多数有关结构优化的工作不同,本文没有讲述成功的故事。经过数天的计算以收集灵敏度和收敛数据,结果表明CSA和CSA M与当今的竞争算法相比,大多数失败。通过表格和曲线图详细讨论了研究的结果,以分享在桁架优化尝试中的不利经验,回顾了通过CSA在结构优化中使用参数控制算法的困难,并为该领域的研究人员节省了时间。

更新日期:2020-05-02
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