Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (19): 64-67.

• 学术探讨 • Previous Articles     Next Articles

New Particle Swarm Optimization strategy for nesting of irregular parts

HUANG Jian-jiang,XU Wen-bo,DONG Hong-wei   

  1. Institute of Information Technology,Southern Yangtze University,Wuxi,Jiangsu 214122,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-07-01 Published:2007-07-01
  • Contact: HUANG Jian-jiang

一种不规则零件排样的新粒子群优化策略

黄建江,须文波,董洪伟   

  1. 江南大学 信息工程学院,江苏 无锡 214122
  • 通讯作者: 黄建江

Abstract: The Particle Swarm Optimization(PSO) with Maximal Velocity Contractile Strategy(MVCS) is applied to the nesting of irregular parts based on the Heuristic Bottom-Left(HBL) algorithm using graphic scan conversion method.The particles of MVCS-PSO are constructed,and the nesting processes of MVCS-PSO and Simulated Annealing Genetic Algorithms(SAGA) are given.MVCS-PSO has the excellent characteristic about the non-linear dynamic search,which is proved by comparing the new combined optimization method to SAGA.Experimental results show that MVCS-PSO is a kind of efficient optimization algorithm for nesting problem.

摘要: 基于图形扫描转换的启发式底左(Heuristic Bottom-Left,HBL)算法,把一种最大速度收缩策略(Maximal Velocity Contractile Strategy,MVCS)的粒子群优化(Particle Swarm Optimization,PSO)算法应用于不规则零件的优化排样,给出了新的排样组合优化算法(MVCS-PSO)的粒子构造方法和零件排样过程,通过实例把该算法与模拟退火遗传算法(Simulated Annealing Genetic Algorithms,SAGA)进行优化排样比较,实验结果表明,具有良好的非线性和动态搜索性能的MVCS-PSO算法是求解排样问题的一种高效算法。