优化遗传算法在复合材料加工中的应用研究

Research on Application of Optimization Genetic Algorithm in Composite Processing

针对传统遗传算法在矩形排样问题应用中存在易陷入局部最优、收敛速率低等不足。对传统遗传算法进行研究,在此基础上引入分阶段调整遗传算子策略加强算法的自适应性,改善搜索性能。并提出融合择优选择策略,保证种群整体质量,进一步提升算法收敛速率。将上述优化后的遗传算法与引入启发式搜索和旋转判断策略的最低水平线算法相结合来解决复合材料在热压成型工序的加工问题。在实证中采用H复合材料加工厂相关零件模具数据对上述方法进行了测试。实验结果表明排样效果显著提升。

In view of the shortcomings of traditional genetic algorithm in the application of rectangular layout problem,it is easy to fall into local optimization and low convergence rate.The traditional genetic algorithm is studied.On this basis,the strategy of adjusting genetic operator in stages is introduced to strengthen the adaptability of the algorithm and improve the search performance.A fusion optimal selection strategy is proposed to ensure the overall quality of the population and further improve the convergence rate of the algorithm.The optimized genetic algorithm is combined with the lowest horizontal line algorithm which introduces heuristic search and rotation judgment strategy to solve the processing problem of composites in hot pressing process.In the demonstration,the above method is tested by using the die data of relevant parts of H composite processing factory.The experimental results show that the layout effect is significantly improved.