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一种求解不确定作业车间调度问题的随机仿真优化方法

王荪馨 李言 张燕荣 淮文博

王荪馨, 李言, 张燕荣, 淮文博. 一种求解不确定作业车间调度问题的随机仿真优化方法[J]. 机械科学与技术, 2015, 34(8): 1211-1216. doi: 10.13433/j.cnki.1003-8728.2015.0813
引用本文: 王荪馨, 李言, 张燕荣, 淮文博. 一种求解不确定作业车间调度问题的随机仿真优化方法[J]. 机械科学与技术, 2015, 34(8): 1211-1216. doi: 10.13433/j.cnki.1003-8728.2015.0813
Wang Sunxin, Li Yan, Zhang Yanrong, Huai Wenbo. A Novel Stochastic Simulation Optimization Method in Solving Job Shop Scheduling Problem Under Processing Time Variability[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(8): 1211-1216. doi: 10.13433/j.cnki.1003-8728.2015.0813
Citation: Wang Sunxin, Li Yan, Zhang Yanrong, Huai Wenbo. A Novel Stochastic Simulation Optimization Method in Solving Job Shop Scheduling Problem Under Processing Time Variability[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(8): 1211-1216. doi: 10.13433/j.cnki.1003-8728.2015.0813

一种求解不确定作业车间调度问题的随机仿真优化方法

doi: 10.13433/j.cnki.1003-8728.2015.0813
基金项目: 

国家自然科学基金项目(51475366)资助

详细信息
    作者简介:

    王荪馨(1974-),副教授,博士研究生,研究方向为先进制造技术、智能优化调度方法,wsx8280@126.com

A Novel Stochastic Simulation Optimization Method in Solving Job Shop Scheduling Problem Under Processing Time Variability

  • 摘要: 针对以工件提前/拖期惩罚成本期望值最小化为目标函数、且工序加工时间不确定条件下的作业车间调度问题,将宽度-深度(BD)仿真量全局优化分配机制嵌入至进化序优化(ESOO)算法框架的粗糙仿真评估阶段。宽度仿真量分配用以调整样本数量,并利用进化算法进行调度解的样本取样和迭代优化;而深度仿真量分配则是利用最优计算量分配技术,依据当前种群中个体的均值和方差进行仿真量的自适应分配。最后通过标准调度测试算例验证了ESOO-BD随机仿真优化方法的可行性和有效性。
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出版历程
  • 收稿日期:  2014-01-18
  • 刊出日期:  2015-08-05

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