中国机械工程

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[云制造]云制造环境下基于贝叶斯网络的机床装备资源优化决策方法

龚小容1;李孝斌2;尹超1   

  1. 1.重庆大学机械传动国家重点实验室,重庆,400030
    2.重庆大学经济与工商管理学院,重庆,400030
  • 出版日期:2018-10-25 发布日期:2018-10-19
  • 基金资助:
    国家自然科学基金资助项目(51705049);
    中国博士后基金资助项目(2017M622975)

Optimization Decision Method of Machine Tool  Resources Based on Bayesian Network under Cloud Manufacturing Environments

GONG Xiaorong1;LI Xiaobin2;YIN Chao1   

  1. 1.State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing,400030
    2.School of Economics and Business Administration,Chongqing University,Chongqing,400030
  • Online:2018-10-25 Published:2018-10-19

摘要: 结合复杂网络理论,提出了一种云制造环境下基于贝叶斯网络的机床装备资源优化选择方法。对云制造环境下机床装备资源优化选择问题进行数学描述,构建了一种由决策环境变量、决策选择变量、决策传递变量、决策目标变量、决策价值变量以及因果依赖关系组成的不确定多阶段多目标(UMM)决策模型,并对该模型的求解算法进行研究;通过实例验证了所提方法的适用性和有效性。

关键词: 云制造, 机床, 贝叶斯网络, 优化决策

Abstract: Combined with complex network theory,an optimal selection method for machine tool resources was proposed based on Bayesian network under cloud manufacturing environments.First,a mathematical description of optimal selection for machine tool resources under cloud manufacturing environments was presented.Then an uncertain multi?stage multi?objective decision model was built,which was composed of decision environmental variables,decision selection variables,decision transfer variables,decision target variables,decision value variables and causal dependency.The solution algorithm of the model was studied.Finally,an example was given to validate the applicability and effectiveness of the proposed method.

Key words: cloud manufacturing, machine tool, Bayesian network, optimization decision

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