基于等基因序列双重随机遗传算法的复合材料铺层优化

复合材料铺层优化中常用的各种遗传算法，较难同时综合考虑表面45°、分层比例、连续铺层数限制等复杂工程约束问题，基于此，提出一种针对复合材料层压板的等基因序列双重随机遗传算法，在交换和突变算子中引入双重随机算法以保证优化迭代中基因序列的严格相等，基于SABRE 软件实现该优化算法，并通过算例验证算法的正确性。结果表明：该算法可满足均衡性、对称性、表面45°、连续铺层数限制、铺层比例等复杂工程约束，有较高的可靠性与工程适用性。

The Isogenic Sequence Double Stochastic Genetic Algorithm Used in Composite Structures

Aiming at various genetic algorithms commonly used in composite layer optimization, it is difficult to comprehensively consider complex engineering constraints such as surface 45 degrees, layering ratio, and continuous layer number limit, this paper proposes an isogenic sequence double random genetic algorithm for composite laminates, which can consider the layering in the optimization. Complex engineering constraints such as ratio, continuous layup limit, adjacent layup angle, surface laying ±45°, etc., the introduction of double random algorithms in the exchange and mutation operators ensures the strict equality of gene sequences in the optimization iteration, and based on the SABRE software The optimization method is realized, the results of calculation and application show that the proposed method can fit complex engineering constraints such as balance, symmetry, surface 45 degrees, continuous ply number limit, ply ratio, etc., and has high reliability and engineering applicability.