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Simultaneous topology, shape and size optimization of truss structures by fully stressed design based on evolution strategy

机译:基于演化策略的全应力设计同时进行桁架结构的拓扑,形状和尺寸优化

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摘要

The most effective scheme of truss optimization considers the combined effect of topology, shape and size (TSS); however, most available studies on truss optimization by metaheuristics concentrated on one or two of the above aspects. The presence of diverse design variables and constraints in TSS optimization may account for such limited applicability of metaheuristics to this field. In this article, a recently proposed algorithm for simultaneous shape and size optimization, fully stressed design based on evolution strategy (FSD-ES), is enhanced to handle TSS optimization problems. FSD-ES combines advantages of the well-known deterministic approach of fully stressed design with potential global search of the state-of-the-art evolution strategy. A comparison of results demonstrates that the proposed optimizer reaches the same or similar solutions faster and/or is able to find lighter designs than those previously reported in the literature. Moreover, the proposed variant of FSD-ES requires no user-based tuning effort, which is desired in a practical application. The proposed methodology has been tested on a number of problems and is now ready to be applied to more complex TSS problems.
机译:桁架优化的最有效方案是考虑拓扑,形状和尺寸(TSS)的综合影响。但是,关于元启发法对桁架优化的大多数可用研究都集中在上述方面中的一两个方面。 TSS优化中各种设计变量和约束的存在可能解释了元启发式方法在该领域的有限适用性。在本文中,最近提出的同时进行形状​​和尺寸优化的算法(基于演化策略(FSD-ES)的全应力设计)经过改进,可以处理TSS优化问题。 FSD-ES将众所周知的全负荷设计确定性方法的优势与对最新发展战略的潜在全球搜索相结合。结果的比较表明,所提出的优化器可以比以前的文献更快地达到相同或相似的解决方案,并且/或者能够找到更轻巧的设计。此外,FSD-ES的拟议变体不需要基于用户的调整工作,这在实际应用中是需要的。所提出的方法已经在许多问题上进行了测试,现在可以应用于更复杂的TSS问题。

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