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Member Sizing Optimization of Large Scale Steel Space Trusses Using a Symbiotic Organisms Search Algorithm
Journal of Physics: Conference Series Pub Date : 2020-09-17 , DOI: 10.1088/1742-6596/1625/1/012019
F T Wong , D Prayogo , R E Putra , J Joseph

A systematic approach of optimization is needed to achieve an optimal design of large and complex truss structures. In the last three decades, several researchers have developed and applied various metaheuristic optimization methods to the design of truss structures. This paper investigates a new metaheuristic algorithm called symbiotic organisms search (SOS) for member sizing optimization of relatively large steel trusses. The case studies include a 120-bar dome truss and a 942-bar tower truss. The structural analyses are carried out using the standard finite element method. The profiles of the truss members are circular hollow structural sections selected from a set of the American Institute of Steel Construction standard profiles. The design results using the SOS are then compared to those obtained using other metaheuristic methods, namely the particle swarm optimization, differential evolution, and teaching-learning-based optimization. The comparison shows the superior performance of the SOS in terms of the optimal solution, consistency, and convergence. Thus, the SOS is a good alternative for optimizing the design of steel truss structures in real engineering practice.



中文翻译:

使用共生生物搜索算法对大型钢空间桁架进行构件尺寸优化

需要一种系统的优化方法来实现大型复杂桁架结构的优化设计。在过去的三十年里,一些研究人员开发并应用了各种元启发式优化方法来设计桁架结构。本文研究了一种称为共生生物搜索 (SOS) 的新元启发式算法,用于对相对较大的钢桁架进行构件尺寸优化。案例研究包括一个 120 杆的圆顶桁架和一个 942 杆的塔式桁架。使用标准有限元方法进行结构分析。桁架构件的型材是选自美国钢结构协会标准型材的圆形空心结构型材。然后将使用 SOS 的设计结果与使用其他元启发式方法获得的设计结果进行比较,即粒子群优化、差分进化和基于教学的优化。比较显示了 SOS 在最优解、一致性和收敛性方面的优越性能。因此,SOS 是在实际工程实践中优化钢桁架结构设计的一个很好的选择。

更新日期:2020-09-17
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