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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Evolutionary structural optimisation (ESO) for combined topology and size optimisation of discrete structures
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Evolutionary structural optimisation (ESO) for combined topology and size optimisation of discrete structures

机译：用于组合拓扑和离散结构尺寸优化的进化结构优化（ESO）

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The single most researched and analysed topic in the field of structural optimisation in the last 40 years has been that of size optimisation for pin- and rigid-jointed frames. Much of the effort has been in developing the search engines that will find a global weight/volume minimum in the presence of multiple constraints, not all of which may be active at the minimum. Most of the algorithmic developments have followed formal mathematical programming techniques. Recently more heuristic methods have emerged for structural optimisation such as genetic algorithms, simulated biological growth and evolutionary algorithms. The authors have been researching the latter mentioned evolutionary structura1 optimisation (ESO) method for the last six years and have found it to be most efficacious for the full range of structural situations; topology, shape and size optimisation with stress, stifftess, frequency, stability constraints in 2D and 3D with single or multiple loads and support conditions. In the present work is a summary of some of our ESO research for pin and rigid-jointed 2D and 3D frames with or without multiple loads. The paper presents the simple evolutionary algorithm and gives examples covering the range of applications. Attention is also given to benchmarking the algorithms and to their reliability and robustness.
机译：在过去的40年中，结构优化领域中最受研究和分析的唯一问题是销钉和刚连接框架的尺寸优化。在开发搜索引擎方面已经做了很多努力，这些搜索引擎将在存在多个约束的情况下找到最小的全局权重/体积，但并非所有的约束都处于最小状态。大多数算法开发都遵循正式的数学编程技术。最近，出现了更多用于结构优化的启发式方法，例如遗传算法，模拟生物生长和进化算法。作者在过去的六年中一直在研究后一种提到的进化结构优化（ESO）方法，发现它对于整个结构情况都是最有效的。通过在单个或多个载荷和支撑条件下的2D和3D中的应力，刚度，频率，稳定性约束来优化拓扑，形状和尺寸。在当前的工作中，我们总结了一些ESO研究的成果，这些研究针对具有或不具有多重负载的销钉和刚性接头2D和3D框架。本文介绍了简单的进化算法，并给出了涵盖应用范围的示例。还注意对算法进行基准测试及其可靠性和鲁棒性。

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