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  

Optimal Scheduling of Irregular Parts Based on Multiple Swarm Genetic Algorithms and Residual Rectangular Matching Algorithms

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9期222-224,共3页Modern Industrial Economy and Informationization

摘　　要：提出一种基于多种群遗传算法和剩余矩形匹配算法的排样优化算法来求解现代工业生产中普遍存在的二维不规则件排样问题。通过提取不规则件的最小包络矩形,将其转化为矩形件排样问题,然后应用多种群遗传算法在全局范围内搜寻可行解,采用剩余矩形匹配算法作为解码算法,将搜索到的可行解解码为排样图,最后进行量化评价,推动种群的进化,找到最优解。实例证明,所提算法优于公司现有排样方法,可提高板材的利用率和排样效率。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]