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The optimisation of space structures using evolution strategies with functional networks

机译:利用功能网络的进化策略优化空间结构

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In this work, the input for large space structures is created using the Formex algebra of the Formian software. The different search and optimisation algorithm known as evolution strategies (ESs) has been applied to find the optimal design of the space trusses considering the areas of the members of the space structures as discrete variables. The objective function is obtained for first few generations by using a structural analysis package such as Feast and for other generations by functional networks (FNs). Initially, to obtain the data for a functional network, a structural package such as Feast is used. The use of a functional network is motivated by time consuming repeated analyses required by evolution strategies during the optimisation process. In addition, a multilevel optimisation approach is implemented by reducing the size of the search space for individual design variables in each successive level of the optimisation process for the first example; for the remaining three examples, a functional network has been combined with evolution strategies to get away with the use of a structural analysis package and a multilevel optimisation technique. The numerical tests presented demonstrate the computational advantage of the proposed approach of ESs combined with functional networks (FNs) which become pronounced for fairly large scale optimisation problems involving about 700 degrees of freedom.
机译:在这项工作中,大型空间结构的输入是使用Formian软件的Formex代数创建的。已将不同的搜索和优化算法(称为进化策略(ESs))用于将空间结构成员的区域视为离散变量的空间桁架的最佳设计。通过使用诸如Feast之类的结构分析包,可以针对前几代获得目标函数,而对于其他几代,则可以通过功能网络(FN)获得目标函数。最初,为了获得功能网络的数据,使用了诸如Feast之类的结构软件包。在优化过程中,进化策略需要耗时的重复分析,从而促使功能网络的使用。此外,通过在第一个示例的优化过程的每个连续级别中减小单个设计变量的搜索空间的大小来实现多级优化方法。对于其余三个示例,功能网络已与进化策略结合在一起,从而摆脱了使用结构分析包和多级优化技术的局面。提出的数值测试证明了所提出的ES与功能网络(FN)结合的方法的计算优势,这对于涉及约700个自由度的相当大规模的优化问题尤为明显。

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