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An improved fully stressed design evolution strategy for layout optimization of truss structures

机译:一种用于桁架结构布局优化的改进的全应力设计演化策略

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摘要

During the recent decade, truss optimization by meta-heuristics has gradually replaced deterministic and optimality criteria-based methods. While they may provide some advantages regarding their robustness and ability to avoid local minima, the required evaluation budget grows fast when the number of design variables is increased. This practically limits the size of the problems to which they can be applied. Furthermore, many recent stochastic optimization methods handle the size optimization only, the potential saving from which is highly limited, when compared to the most sophisticated, and obviously the most challenging scenario, simultaneous topology, shape and size (TSS) optimization. In a recent study by the authors, a method based on combination of optimality criteria and evolution strategies, called fully stressed design based on evolution strategies (FSD-ES), was proposed for TSS optimization of truss structures. FSD-ES outperformed available truss optimizers in the literature, both in efficiency and robustness. The contribution of this study is twofold. First, an improved version of FSD-ES method, called FSD-ES-II, is proposed. In comparison with the earlier version, it takes the displacement constraints in the resizing step into account and can handle constraints governed by practically used specifications. Update of strategy parameters is also revised following contemporary and new developments in evolution strategies. Second, a test suite involving a number of complicated TSS optimization problems is chosen to overcome usual shortcomings in the available benchmark problems. For each problem, performance of FSD-ES-II is compared with the best results available in the literature, often showing a significant superiority of the proposed approach. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在最近的十年中,基于元启发式的桁架优化逐渐取代了基于确定性和最优性标准的方法。尽管它们可能在健壮性和避免局部最小值方面提供一些优势,但随着设计变量数量的增加,所需的评估预算也会快速增长。这实际上限制了可以解决的问题的大小。此外,与最复杂,显然也是最具挑战性的方案,同时进行拓扑,形状和尺寸(TSS)优化相比,许多最新的随机优化方法仅处理尺寸优化,因此节省的潜力非常有限。在作者最近的研究中,提出了一种基于最优准则和演化策略相结合的方法,称为基于演化策略的全应力设计(FSD-ES),用于桁架结构的TSS优化。 FSD-ES在效率和鲁棒性方面均优于文献中可用的桁架优化器。这项研究的贡献是双重的。首先,提出了一种改进的FSD-ES方法,称为FSD-ES-II。与早期版本相比,它在调整大小步骤中考虑了位移约束,并且可以处理实际使用的规范所约束的约束。策略参数的更新也随着进化策略的最新发展而进行了修订。其次,选择一个涉及许多复杂的TSS优化问题的测试套件,以克服可用基准测试问题中的常见缺陷。对于每个问题,将FSD-ES-II的性能与文献中可获得的最佳结果进行比较,通常显示出所提出方法的显着优势。 (C)2015 Elsevier Ltd.保留所有权利。

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