Modified genetic algorithm for optimal design of truss structures

Mechanics Pub Date : 2024-04-04 DOI:10.5755/j02.mech.36227
D. Šešok, R. Belevičius
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引用次数: 5

Abstract

In this paper, topology and shape optimization of truss or frame structures is discussed. The optimization starts from a structure, into which a finite number of nodesare set; all the nodes are connected together by trusses in all possible variants. Unfit variants of the truss system are rejected. Two alternative ways of the optimization are compared: topology optimization starting from initial structure with a larger number of nodes, and topology optimization starting from initial structure with smaller number of nodes but with additional shape optimization of the obtained topology. The topology optimization is solved with original modified genetic algorithm, giving better results in comparison with classical genetic algorithm. Instead of further development of constraint system, the additional step is introduced into algorithm – purification of genotype, which allows complementary improvement of particular population individuals, and together for the optimization process retains more possibilities than stiffening of constraints. The shape optimization is solved by classical genetic algorithm. Both strategies effectively improve the solution, however the common topology/shape optimization requires less computer resources. All numerical examples are obtained with original software developed by the authors.
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桁架结构优化设计的改进遗传算法
本文讨论了桁架或框架结构的拓扑和形状优化。优化从一个结构开始,其中设置了有限数量的节点;所有节点通过桁架以各种可能的形式连接在一起。不合适的桁架系统将被剔除。比较了两种可供选择的优化方法:从节点数较多的初始结构开始进行拓扑优化,以及从节点数较少的初始结构开始进行拓扑优化,但对获得的拓扑结构进行额外的形状优化。拓扑优化采用原始改进遗传算法求解,与经典遗传算法相比结果更好。该算法没有进一步发展约束系统,而是引入了额外的步骤--纯化基因型,这使得特定群体个体得到了补充性改进,同时在优化过程中保留了比强化约束更多的可能性。形状优化由经典遗传算法解决。这两种策略都能有效地改进解法,但共同的拓扑/形状优化所需的计算机资源较少。所有数值示例都是通过作者开发的原创软件获得的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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