JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

Volume 35 Issue 6
December 2020
Article Contents
WEN Xiaoyu, WANG Kanghong, LI Hao and et al. Simulation and optimization of job shop scheduling with place buffer under uncertain disturbances[J]. Journal of Light Industry, 2020, 35(6): 84-92. doi: 10.12187/2020.06.010
Citation: WEN Xiaoyu, WANG Kanghong, LI Hao and et al. Simulation and optimization of job shop scheduling with place buffer under uncertain disturbances[J]. Journal of Light Industry, 2020, 35(6): 84-92. doi: 10.12187/2020.06.010 shu

Simulation and optimization of job shop scheduling with place buffer under uncertain disturbances

  • Received Date: 2020-05-15
  • Aiming at the problem that the uncertain disturbance factors in the workshop production have an impact on the real-time execution of the scheduling scheme, a job shop scheduling scheme with place buffer under uncertain disturbance was proposed to deal with the disturbance factors in the production workshop system combining simulation technology with intelligent optimization algorithm.Normally distributed random variables were utilized to describe uncertain processing time, and uniformly distributed intervals were employed to describe the average failure interval time and average repair time.The place buffer's parameters before severely blocked equipment were adjusted to affect the maximum completion time.An uncertain scheduling simulation model for job shop production was constructed by Plant Simulation software and genetic algorithm was used to solve the model.The simulation results showed that the adjustment of the place buffer's time parameter could obtain the best fitness value, which verified that the proposed method could effectively reduce the impact caused by uncertain processing time and random machine failures during the workshop production scheduling.
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    1. [1]

      李明辉,石宇强,王俊佳,等.基于Em-plant的包装制造生产系统仿真研究[J].制造业自动化,2015,37(23):24.

    2. [2]

      曹庆奎,张晓丽,任向阳,等.基于GASA的柔性作业车间动态调度研究[J].河北工程大学学报(自然科学版),2019,36(2):91.

    3. [3]

      戴伯尧.基于Plant Simulation模具生产车间调度策略仿真研究[D].广州:广东工业大学,2012.

    4. [4]

      王军强,陈剑,翟颖妮,等.扰动情形下瓶颈利用对作业车间调度的影响[J].计算机集成制造系统,2010,16(12):138.

    5. [5]

      曾程宽,刘士新.缓冲区间有限条件下的作业车间调度方法[J].东北大学学报(自然科学版),2018,39(12):1679.

    6. [6]

      白立浩.定制化制造企业车间调度策略与仿真研究[D].徐州:中国矿业大学,2015.

    7. [7]

      李云龙,罗国富,文笑雨,等.基于混合遗传算法的云制造环境下柔性作业车间调度方案[J].轻工学报,2020,35(3):99.

    8. [8]

      崔晶,李慧.基于Plant Simulation的航空复合材料生产线工艺布局仿真建模及评估[J].航空制造技术,2019,62(4):56.

    9. [9]

      唐秋华,何明,何晓霞.随机工时下柔性加工车间的鲁棒优化调度方法[J].计算机集成制造系统,2015,21(4):1002.

    10. [10]

      陈宇轩.工时不确定条件下基于改进遗传算法的柔性作业车间调度问题的区间数求解方法[J].机械工程师,2018(1):74.

    11. [11]

      张国辉,吴立辉,聂黎.考虑机器故障的柔性作业车间鲁棒调度方法[J].系统仿真学报,2016,28(4):867.

    12. [12]

      施於人.eM-Plant仿真技术教程[M].北京:科学出版社,2009.

    13. [13]

      LI X Y,GAO L,WEN X Y.Application of an efficient modified particle swarm optimization algorithm for process planning[J].International Journal of Advanced Manufacturing Technology,2013,67(5/6/7/8):1355.

    14. [14]

      文笑雨,罗国富,李浩.两阶段混合算法求解集成工艺规划与调度问题[J].中国机械工程, 2018, 29(22):74.

    15. [15]

      周金平.生产系统仿真——Plant Simulation应用教程[M].北京:电子工业出版社,2011.

    16. [16]

      LUO G F,WEN X Y,LI H,et al.An effective multi-objective genetic algorithm based on immune principle and external archive for multi-objective integrated process planning and scheduling[J].The International Journal of Advanced Manufacturing Technology,2017,91(9/10/11/12):3145.

    17. [17]

      文笑雨.多目标集成式工艺规划与车间调度问题的求解方法研究[D].武汉:华中科技大学,2014.

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