基于双种群遗传算法的含缺陷矩形件排样优化研究

Research on Layout Optimization of Defective Rectangular Parts Based on Dual Population Genetic Algorithm

结合缺陷约束的最低水平线算法与双种群遗传算法,对板材内部含缺陷时的情况进行矩形件排样优化。用双种群遗传算法对矩形件排样顺序进行寻优,将矩形件的排样顺序和旋转方式划分为2个种群分别进行遗传迭代,并结合改进的初始种群生成策略,改善算法的搜索效率及全局寻优能力。基于缺陷约束的最低水平线算法通过更新缺陷矩形轮廓信息与引入缺陷位置约束判断,使矩形件在根据优化顺序排样时可避开缺陷部位。通过算例运算测试可知,相比于经典遗传算法,所提算法在4种不同数量缺陷的板材中,最优板材利用率与排样优化稳定性均有所提高。双种群遗传算法和基于缺陷约束的最低水平线算法可在含缺陷板材的排样问题中得到推广应用。

The minimum horizontal line algorithm with defect constraints is combined with a double-population genetic algorithm to optimize the layout of rectangular parts with defects in the plate.The double-population genetic algorithm is used to optimize the layout order of rectangular parts.The layout order and rotation mode of rectangular parts are divided into two populations for genetic iteration respectively.Combined with the improved initial population generation strategy,the search efficiency and global optimization ability of the algorithm are improved.The minimum horizontal line algorithm based on the defect constraint can avoid the defective position when the rectangular parts are arranged according to the optimized order by updating the contour information of the defective rectangle and introducing the defective position constraint judgment.Through the calculation of the examples,it can be seen that compared with the traditional genetic algorithm,the optimal plate utilization rate and layout optimization stability of the algorithm in this paper are improved in four kinds of plates with different number of defects.The double-population genetic algorithm and the lowest horizontal line algorithm based on defect constraint can be applied to the problem of panel layout with defects.