【摘要】 针对现代制造业中广泛存在的不规则排样问题进行了研究,提出一种基于临界多边形排样策略和小生境遗传算法的排样优化算法.算法通过改进的移动碰撞法计算零件之间的临界多边形,以确定最佳的零件靠接排放位置;通过基于小生境策略的遗传算法优化零件的排样顺序,确定最佳排样序列.对所提出的排样优化算法作了实验测试和算法评估,验证算法的可行性与有效性.排样实验结果表明,该算法能够用于求解不规则排样问题,且在一定程度上优于已有算法,能够提高材料利用率.更多还原

【Abstract】 For the issue of irregular packing problem widely existed in modern manufacturing,this paper conducted a study on it and presented a packing optimization algorithm based on no-fit polygon method and niche genetic algorithm. The algorithm calculates nofit polygon between two parts by the improved collision approach to determine the best packing position for the part,and searches for the optimal packing order by genetic algorithm based on niche strategy. Experimental test was performed to verify and evaluate feasibility and efficiency of the proposed optimization algorithm. The results of packing test showthat the proposed algorithm can solve the irregular packing problem,provide better results than existing algorithm to some extent and improve utilization of material.更多还原