中国机械工程 ›› 2013, Vol. 24 ›› Issue (16): 2195-2201.

• 制造系统 • 上一篇    下一篇

基于双层遗传编码的柔性作业车间自适应重调度研究

李平1,2;唐秋华1;夏绪辉1;陈平和3   

  1. 1.武汉科技大学,武汉,430081
    2.湖北理工学院,黄石,435000
    3.武汉神龙汽车公司技术中心,武汉,430056
  • 出版日期:2013-08-25 发布日期:2013-08-23
  • 基金资助:
    国家自然科学基金资助项目(50875190)
    National Natural Science Foundation of China(No. 50875190)

Self-adaptively Rescheduling Flexible Job Shop with Double Genetic Coding

Li Ping1,2;Tang Qiuhua1;Xia Xuhui1;Chen Pinghe3   

  1. 1.Wuhan University of Science and Technology,Wuhan,430081
    2.Hubei Polytechnic University,Huangshi,Hubei,435000
    3.Technique Center of Dongfeng Peugeot Citroen Automobile Company,Wuhan,430056
  • Online:2013-08-25 Published:2013-08-23
  • Supported by:
    National Natural Science Foundation of China(No. 50875190)

摘要:

针对不确定环境下的柔性作业车间调度,设计了能适应订单异动、操作延时和机器故障等3种常见扰动类型的重调度方法。通过设置可用机器集和操作时间等基本参数,制定各扰动单独或组合发生后基本参数的更新策略,建立了面向3种不确定扰动类型的自适应重调度框架;结合工序码和机器码形成了一
种双层染色体编码,该编码能有效表征上述系统参数,实现自适应重调度;利用遗传算法,通过选择算子寻优及交叉变异算子的种群拓展实现全局优化。400个具有不同规模的实例证明了该重调度方法所得方案可信,计算时间可控,能有效应用于生产实际。

关键词: 柔性作业车间, 重调度, 遗传算法, 自适应

Abstract:

Aiming at three kinds of uncertain disturbances appearing
frequently within flexible Job Shop,i. e. order changes,operation delays and machine breakdown,a novel rescheduling approach was designed.First,a self-adaptive rescheduling framework was constructed after setting up a set of system  parameters including
optional machines and operation times,and formulating strategies about updating systematical parameters under single or multiple
disturbances.Second,codes for depicting job sequence and machine assignment
 were combined together in double genetic chromosomes to encode the above system
parameters so as to execute self-adaptive rescheduling.Third,through genetic
algorithm,better solutions were inherited by selection operators and the population of
each generation was expanded gradually via crossover and mutation operators,
and hence global optimization was achieved effectively.Experimental studies with 400
cases from small to large scale verify that near-optimal reschedule can be obtained
under controllable computational times and thus can be applicable in practice. 

Key words: flexible Job Shop, rescheduling, genetic algorithm, self-adaptive

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