基于多种群遗传算法和剩余矩形匹配算法不规则件优化排样  

Multi-Population Adaptive Genetic Algorithm is Used to Solve Irregular Layout Problem

作　　者：秦振浩 Qin Zhenhao(School of Economics and Management,Hebei University of Technology,Tianjin 300400)

机构地区：[1]河北工业大学经济管理学院,天津300400

出　　处：《现代工业经济和信息化》2022年第12期262-264,共3页Modern Industrial Economy and Informationization

摘　　要：以钣金件排样过程为应用背景,通过对不规则件进行预处理,求出不规则件的最小包络矩形,把不规则排样转化为矩形件正交排样,结合多种群遗传算法和剩余矩形匹配算法进行优化排样,找到问题的最优解,确定零件在板材上的合理排放位置。实例证明,该算法能够提高板材的利用率和排样效率,降低企业的生产成本。A layout optimization algorithm based on multi-population genetic algorithm and residual rectangle matching algorithm was proposed to solve the 2D irregular layout problem in modern industrial production. By extracting the smallest rectangle of irregular parts and convert it into rectangles layout problem,and then based on multiple population genetic algorithm to search for feasible solution in the global scope,the surplus rectangle matching algorithm for decoding algorithm,to search the feasible solution of decoding for layout diagram,finally carries on the quantitative evaluation,to promote the evolution of the population,to find the optimal solution. Examples show that the proposed algorithm is superior to the company’s existing layout method,can improve the utilization rate of plate and strip layout efficiency.

关 键 词：多种群遗传算法 剩余矩形匹配算法 矩形包络法 不规则件排样 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]