基于粒子群算法的二维不规则排样  

Two-dimensional Irregular Layout Based on Particle Swarm Optimization Algorithm

作　　者：吕万林 游有鹏[1] LYU Wanlin;YOU Youpeng(College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学机电学院,江苏南京210016

出　　处：《机械制造与自动化》2024年第4期165-168,186,共5页Machine Building & Automation

摘　　要：针对工业生产中常见的二维不规则排样问题,提出运用粒子群算法求解的方法。将BL算法和NFP算法结合,作为排样定位策略;对工件的入排顺序和入排角度进行编码,进行粒子群算法优化求解,并通过交叉替代传统的插值改进粒子位置更新过程,满足排样的离散问题求解;通过添加粒子的变异过程,避免陷入局部最优解。算例排样结果验证了该算法的有效性。A method to solve the common two-dimensional irregular layout problem in industrial production by particle swarm optimization algorithm is proposed.BL algorithm and NFP algorithm are combined as the positioning strategy.The input order and input angle of the workpiece are coded,and the particle swarm optimization algorithm is used to optimize the solution.By replacing the traditional interpolation with intersection,the process of particle position updating is improved to solve the discrete problem of layout.The mutation process of particles is added to avoid the local optimal solution.The sample layout result verifies the effectiveness of the proposed algorithm.

关 键 词：二维不规则排样 BL算法 NFP算法 粒子群算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]