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Optimal design of large-scale space steel frames using cascade enhanced colliding body optimization

机译:大型空间钢帧的优化设计使用级联增强碰撞体优化

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In structural size optimization usually a relatively small number of design variables is used. However, for large-scale space steel frames a large number of design variables should be utilized. This problem produces difficulty for the optimizer. In addition, the problems are highly non-linear and the structural analysis takes a lot of computational time. The idea of cascade optimization method which allows a single optimization problem to be tackled in a number of successive autonomous optimization stages, can be employed to overcome the difficulty. In each stage of cascade procedure, a design variable configuration is defined for the problem in a manner that at early stages, the optimizer deals with small number of design variables and at subsequent stages gradually faces with the main problem consisting of a large number of design variables. In order to investigate the efficiency of this method, in all stages of cascade procedure the utilized optimization algorithm is the enhanced colliding bodies optimization which is a powerful metaheuritic. Three large-scale space steel frames with 1860, 3590 and 3328 members are investigated for testing the algorithm. Numerical results show that the utilized method is an efficient tool for optimal design of large-scale space steel frames.
机译:在结构尺寸优化中,通常使用相对少量的设计变量。但是,对于大型空间钢框架,应使用大量的设计变量。此问题对优化器产生了难度。此外,问题是高度非线性的,结构分析需要大量的计算时间。级联优化方法的想法允许在多个连续的自主优化阶段进行单一优化问题,可以采用克服困难。在级联过程的每个阶段,以早期阶段的方式定义了设计变量配置,优化器在少量的设计变量和随后的阶段逐渐遵守大量设计的主要问题变量。为了探讨该方法的效率,在级联程序的所有阶段,利用优化算法是增强的碰撞体优化,这是一种强大的成形素质。研究了具有1860,3590和3328个成员的三个大型空间钢框架,用于测试算法。数值结果表明,利用方法是大型空间钢框架最优设计的有效工具。

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