• 论文 •    

求解柔性车间作业调度的知识型协同演化方法

贺仁杰,陈宇宁,姚锋,邢立宁   

  1. 国防科技大学 信息系统与管理学院管理系,湖南长沙410073
  • 出版日期:2011-02-25 发布日期:2011-02-25

Knowledge-based co-evolutionary approach for flexible Job Shop scheduling

HE Ren-jie, CHEN Yu-ning, YAO Feng, XING Li-ning   

  1. Department of Management, College of Information Systems & Management,National University of Defense Technology, Changsha 410073, China
  • Online:2011-02-25 Published:2011-02-25

摘要: 提出了一种求解柔性车间作业调度的知识型协同演化方法。在该方法中,各个种群采用不同的进化方法和参数设置来推进各自的演化进程;种群之间通过相互的资源竞争和信息共享,共同推动整体算法的进化进程。采用柔性作业车间调度问题的15个标准实例进行实验,结果表明所提方法在优化性能方面优于近期公开发表的七种典型方法。

关键词: 柔性作业车间调度, 遗传算法, 蚁群算法, 协同演化

Abstract: A knowledge-based co-evolutionary approach was proposed to solve the flexible Job Shop scheduling problems. In this approach, both the ant colony optimization and parameter configuration were applied to facilitate evolution of each population independently. By interactive resource competition and information sharing mechanism among populations, the evolution process of entire algorithm was promoted. Performance of this approach was evaluated by some benchmark examples taken from literature. Experimental results suggested that this approach outperformed seven recently published approaches.

Key words: flexible Job Shop scheduling, genetic algorithms, ant colony optimization, co-evolutionary

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