面向智能制造的不规则零件排样优化算法  

Optimization algorithm of irregular parts layout for intelligent manufacturing

作　　者：高勃 张红艳 朱明皓[2] GAO Bo;ZHANG Hongyan;ZHU Minghao(School of Computer and Information Technology, Beijing Jiaotong University,Beijing 100044, China;School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

机构地区：[1]北京交通大学计算机与信息技术学院,北京100044 [2]北京交通大学经济管理学院,北京100044

出　　处：《计算机集成制造系统》2021年第6期1673-1680,共8页Computer Integrated Manufacturing Systems

摘　　要：以智能工厂应用场景为例,为提高广泛应用于智能制造领域的二维不规则件的排样性能,提出了基于启发式和蚁群的不规则件排样优化算法。首先提取不规则件的几何特征,对零件进行组合操作预处理,使两个或多个不规则零件组合为矩形件或近似矩形件并对其包络矩形,然后利用蚁群学习算法对预处理后的零件进行排样,确定零件排放的最佳位置,不断更新得到最优排样结果。仿真实验结果表明,综合考虑板材利用率以及耗时情况,所提算法取得了较好的结果,能够满足实际生产的需求。To improve the performance of two-dimensional irregularly shaped part layout in the field of intelligent manufacturing and smart factories,an optimization algorithm based on heuristics and ant colony optimizations was proposed.The geometric features of irregularly shaped parts were extracted to preprocess combinatorial operation of these parts,which made two or more parts combine into rectangular or approximately rectangular parts.Then the ant colony learning algorithm was used to find an initial combination of parts.After irregularly shaped parts are nested,the best position of each part was determined and optimized iteratively.The results of simulation experiments showed that the algorithm had achieved satisfactory results in terms of the utilization rate of boards and time-complexity,which made a reasonable solution to be adopted for actual productions.

关 键 词：二维板材 不规则零件 启发式算法 蚁群学习算法 优化排样 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]