计算机应用 ›› 2012, Vol. 32 ›› Issue (04): 1022-1024.DOI: 10.3724/SP.J.1087.2012.01022

• 人工智能 • 上一篇    下一篇

改进的粒子群算法求解置换流水车间调度问题

张其亮1,2,陈永生2,韩斌1   

  1. 1. 江苏科技大学 电气与信息工程学院,江苏 张家港 215600
    2. 同济大学 电子与信息工程学院,上海 200331
  • 收稿日期:2011-10-13 修回日期:2011-12-05 发布日期:2012-04-20 出版日期:2012-04-01
  • 通讯作者: 张其亮
  • 作者简介:张其亮(1979-),男,山东潍坊人,讲师,博士研究生,主要研究方向:智能算法优化;陈永生(1966-),男,江苏镇江人,教授,博士,主要研究方向:智能算法优化、轨道交通;韩斌(1968-),男,江苏南通人,教授,博士,主要研究方向:数字图像处理、算法优化。
  • 基金资助:
    国家“十一五”科技支撑项目

Improved particle swarm optimization for permutation flowshop scheduling problem

ZHANG Qi-liang1,2,CHEN Yong-sheng2,HAN Bin1   

  1. 1. College of Electricity and Information Engineering, Jiangsu University of Science and Technology, Zhangjiagang Jiangsu 215600, China
    2. College of Electronic and Information Engineering,Tongji University, Shanghai 200331,China
  • Received:2011-10-13 Revised:2011-12-05 Online:2012-04-20 Published:2012-04-01
  • Contact: ZHANG Qi-liang

摘要: 针对置换流水车间调度问题,提出了一种改进的粒子群算法进行求解。改进算法引入了判断粒子群早熟的方法,并在发现粒子群早熟后采用逆转策略对种群最优粒子进行变异,利用模拟退火思想概率接收新的最优粒子。种群最优粒子的改变会引导粒子群跳出局部极值的约束,从而克服粒子群的早熟状态。通过对置换流水车间调度问题中Car系列和Rec系列部分基准数据的测试,证明了该算法的有效性。

关键词: 粒子群算法, 多样性, 局部收敛, 置换流水车间调度

Abstract: To solve permutation flowshop scheduling problem, an improved particle swarm optimization was proposed. Improved algorithm introduced a method to judge the premature state of the particle swarm, and used reversion strategy to mutate the best particle after the particle swarm being trapped in premature convergence, and used simulated annealing method to accept the new particle. The mutation for best particle can guide the particle swarm to escape from the local best values limit and overcome the particles premature stagnation. The simulation results based on Car and Rec benchmarks of permutation flowshop scheduling problem prove the effectiveness of the proposed algorithm.

Key words: Particle Swarm Optimization (PSO), diversity, local convergence, permutation flowshop scheduling