基于混合遗传算法的复合材料结构优化空间应用

L. Gharsalli, Yannick Guerin
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摘要

本研究的目的是开发一种混合遗传算法(H-GA),该算法将遗传算法(GA)与下降局部搜索技术相结合,以追求位于发射器上界的夹层复合材料级间裙的优化。形成夹层复合材料表面的层数和纤维方向(预先定义的层角)被认为是设计变量。选择H-GA作为优化工具是因为它能够处理离散优化问题,复合材料堆积设计就是一个例子。首先,提出并解释了所提出的方法。然后,将其性能与经典遗传算法进行了比较和讨论。本研究的目的是开发一种混合遗传算法(H-GA),该算法将遗传算法(GA)与下降局部搜索技术相结合,以追求位于发射器上界的夹层复合材料级间裙的优化。形成夹层复合材料表面的层数和纤维方向(预先定义的层角)被认为是设计变量。选择H-GA作为优化工具是因为它能够处理离散优化问题,复合材料堆积设计就是一个例子。首先,提出并解释了所提出的方法。然后,将其性能与经典遗传算法进行了比较和讨论。
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Composite structures optimization using hybrid genetic algorithm for space applications
The aim of this study is to develop a hybrid genetic algorithm (H-GA) that combines a genetic algorithm (GA) and a descent local search technique to pursue the optimization of a sandwich composite inter-stage skirt located in the upper bound of the launcher. Total number of plies forming the sandwich composite skin and fiber orientations (predefined ply angles) are considered as design variables. The H-GA is chosen as an optimization tool thanks to its ability to deal with discrete optimization problems, of which the design of composites stacking is an example. First, the proposed approach is presented and explained. Then, its performances are compared and discussed against those offered by the classical GA.The aim of this study is to develop a hybrid genetic algorithm (H-GA) that combines a genetic algorithm (GA) and a descent local search technique to pursue the optimization of a sandwich composite inter-stage skirt located in the upper bound of the launcher. Total number of plies forming the sandwich composite skin and fiber orientations (predefined ply angles) are considered as design variables. The H-GA is chosen as an optimization tool thanks to its ability to deal with discrete optimization problems, of which the design of composites stacking is an example. First, the proposed approach is presented and explained. Then, its performances are compared and discussed against those offered by the classical GA.
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