基于迷宫问题遗传算法的复合材料铺层数量优化

研究使用最少铺层数量,使产品达到性能指标的复合材料铺层优化问题。使用遗传算法,参考迷宫问题的解决方法,保留普通遗传算法的框架,改变求染色体的适应度值的计算过程,找出满足要求的最少铺层数量的解。在求适应度值过程中增加逐位解释环节,以得不同铺层数量的解。在求适应度值过程中增加解码、剔除无效项、对称环节,以满足复合材料铺层角角度离散、铺层角要少于4层连续相同、对称这些常见要求。结合示例,指出将逐位解释范围分段,可以提高计算效率。该方法实现了对复合材料产品的铺层数量和角度的同时优化,可以实现产品的经济性和轻量化。

Stacking number optimization of composite product by genetic algorithm based on maze problem

This composite stacking optimization aims at the product meeting the target with least layers.Using genetic algorithm, referring to the solution to the maze problem, retaining the framework of the common genetic algorithm, changing the chromosome fitness value calculation process, the solution which has the minimum number of layers and meet the requirements was found.In the fitness value calculation process,the bit by bit explanation was added, to get solutions with various numbers of layers.In the fitness value calcula- tion process, the encoding,removing invalid entries, symmetrization was added to meet the common requirements such as ply angles discrete, less than four contiguous plies in same direction, and symmetric.It pointed out with an example, that sectioning the range of the bit by bit explanation will improve efficiency. This method optimizes the stacking layer number and angles at the same time, which will achieve economical and lightweight.