渐进演化类拓扑优化算法的优化准则对比研究
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TU318

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国家自然科学基金(51508182);湖南省大学生研究性学习和创新性实验计划(201712649001)


Comparative study on optimization criteria of evolutionary topology optimization algorithms
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    摘要:

    渐进演化类拓扑优化算法的优化准则是影响结构优化结果的关键因素之一。以不同荷载和边界条件下的深梁模型为数值算例,比较了基于不同优化准则的3种算法在优化解和优化效率上的差别。结果表明:对于荷载和边界等条件较简单的构件,采用单向和确定性优化准则的渐进演化类拓扑优化算法能高效地得到最优拓扑,采用概率性优化准则和采用双向优化准则的渐进演化类拓扑优化算法有着更广的适用范围,在荷载和边界等条件较复杂的构件上,同样表现出较强的避免优化畸变的能力和全局寻优能力。对结合概率性优化准则和双向优化准则的遗传双向渐进演化结构优化算法建立了流程图,并进行初步讨论,以期进一步提高渐进演化类拓扑优化算法的实用性和寻优能力。

    Abstract:

    The optimization criterion of evolutionary topology optimization algorithms is one of the key factors affecting the structural optimization results. In this paper, some deep beam models under different load and boundary conditions are taken as a numerical examples, and comparing the difference between the optimization solution and the computational efficiency of the three algorithms based on different optimization criteria. The results show that the evolutionary topology optimization algorithms based on one-way optimization criteria and deterministic optimization criteria can efficiently obtain the optimal topology for components with simple conditions such as load and boundary, and the evolutionary topology optimization algorithms based on probabilistic optimization criterion or bidirectional optimization criterion have a stronger scope of application, and it also shows a strong ability to avoid optimized distortion and conduct global optimization on components with complicated conditions such as load and boundary. At the end of this paper, a flow chart is established for the genetic bidirectional evolutionary structural optimization algorithm combining probabilistic optimization criterion and bidirectional optimization criterion. The preliminary discussion is carried out to further improve the practicability and optimization ability of evolutionary structural optimization algorithm.

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张鹄志,张棒,谢献忠,马哲霖.渐进演化类拓扑优化算法的优化准则对比研究[J].土木与环境工程学报(中英文),2020,42(3):73-79.

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  • 收稿日期:2019-07-08
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  • 在线发布日期: 2020-06-13
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