东北大学学报(自然科学版) ›› 2008, Vol. 29 ›› Issue (4): 565-568.DOI: -

• 论著 • 上一篇    下一篇

基于粒子群算法的车间调度与优化

何利;刘永贤;谢华龙;刘笑天;   

  1. 东北大学机械工程与自动化学院;东北大学机械工程与自动化学院;东北大学机械工程与自动化学院;东北大学机械工程与自动化学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2008-04-15 发布日期:2013-06-22
  • 通讯作者: He, L.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60475036)

Job shop scheduling and its optimization based on particle swarm optimizer

He, Li (1); Liu, Yong-Xian (1); Xie, Hua-Long (1); Liu, Xiao-Tian (1)   

  1. (1) School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2008-04-15 Published:2013-06-22
  • Contact: He, L.
  • About author:-
  • Supported by:
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摘要: 通过对车间调度问题的描述,针对传统调度算法寻优效率低或全局寻优能力差的弱点,提出了一种基于粒子群算法(PSO)的车间调度问题解决方案.根据车间调度问题的特点,对粒子群的编码及寻优操作进行了研究,确定了更适合车间调度问题的编码和操作方式,并将算法进行编程,应用到了系统的车间调度部分.仿真结果表明,通过设置适当的参数,可以快速地得到很好的排序结果,能够适用于动态的车间调度问题.

关键词: 生产管理系统, 车间调度, 智能优化算法, 粒子群算法, 动态调度

Abstract: Considering the conventional algorithms' low efficiency of search especially global search, PSO-based solution to job shop scheduling problem is presented. According to the characteristics of the problem, the PSO coding and optimization are studied to determine the way of coding and operation, which is more adaptable to job shop scheduling. The job shop scheduling part of the system is then programmed with the algorithm. Simulation results showed that setting the suitable parameters can provide an excellent working sequence to adapt to the dynamic job-shop problem.

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