面向利用率的矩形排样分级进化遗传算法优化  

Rectangle Packing Optimization Based on Hierarchical Evolution Genetic Algorithm to Improve Plate Utilization

作　　者：冯建云 刘祎[2] FENG Jian-yun;LIU Yi(Department of Computer Engineering,Shanxi College of Architectural,Shanxi Taiyuan 030600,China;Suqian College,Jiangsu Suqian 223800,China)

机构地区：[1]山西建筑职业技术学院计算机工程系,山西太原030600 [2]宿迁学院,江苏宿迁223800

出　　处：《机械设计与制造》2022年第11期11-16,共6页Machinery Design & Manufacture

基　　金：2019年度市级指导性科技计划项目(Z2019108)。

摘　　要：为了提高矩形排样的板材使用率,提出了基于分级进化遗传算法的排样优化方法。以板材利用率最高为目标建立了矩形排样的目标模型,将排样问题分为定位和排序两个步骤实现。在定位方面,将最低水平线法和填充算法进行优势融合,得到了混合定位方法。在排序方面,以遗传算法为基础,将染色体分为保留层级、交叉层级和变异层级等3个层级,每个层级制定相适应的进化操作方法,从而提高算法的搜索能力和收敛速度。使用文献[13]和文献[14]中的两组实验数据进行验证,结果表明这里提供的排样方案可以得到最佳的排样结果,且排样耗时最少。验证了这里分级进化遗传算法排样方法的有效性和高效性。In order to improve the utilization rate of rectangular layout,a layout optimization method based on hierarchical evolutionary genetic algorithm was proposed.Aiming at the highest utilization rate of sheet metal,the objective model of rectangular layout is established,and the layout problem is divided into two steps:positioning and sequencing.In the aspect of location,the minimum horizontal line method and filling algorithm are combined to get a hybrid location method.In the aspect of sequencing,based on genetic algorithm,the chromosome is divided into three levels,including reservation level,crossover level and mutation level.Each level formulates the appropriate evolutionary operation method,so as to improve the search ability and convergence speed of the algorithm.Two groups of experimental data in literature[13]and literature[14]are used to verify the results.The results show that the layout scheme proposed in this paper can get the best layout results,and the layout time is the least.The results verify the effectiveness and efficiency of this method.

关 键 词：矩形件排样 分级进化遗传算法 混合定位方法 板材利用率 

分 类 号：TH16[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]