基于云制造平台的供应链生产计划方法
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  • 英文篇名:Production Planning Method of Supply Chain Based on Cloud Manufacturing Platform
  • 作者:孔继利 ; 曹文颖 ; 杨福兴
  • 英文作者:KONG Ji-li;CAO Wen-ying;YANG Fu-xing;Automation School,Beijing University of Posts and Telecommunications;School of Economics and Management,Beihang University;
  • 关键词:云制造平台 ; 供应链 ; 生产计划 ; 改进遗传退火算法
  • 英文关键词:cloud manufacturing platform;;supply chain;;production plan;;improved genetic-annealing algorithm
  • 中文刊名:BJYD
  • 英文刊名:Journal of Beijing University of Posts and Telecommunications
  • 机构:北京邮电大学自动化学院;北京航空航天大学经济管理学院;
  • 出版日期:2018-03-29 09:41
  • 出版单位:北京邮电大学学报
  • 年:2018
  • 期:v.41
  • 基金:国家自然科学基金项目(71772010);; 北京邮电大学青年科研创新计划专项-人才项目(2017RC26)
  • 语种:中文;
  • 页:BJYD201802003
  • 页数:6
  • CN:02
  • ISSN:11-3570/TN
  • 分类号:19-24
摘要
提出了一种基于云制造平台的供应链生产计划方法.构建了以最大完工时间、总服务成本和总运输成本为优化目标的供应链生产计划模型,设计了遗传算法和改进遗传退火算法,对模型进行求解,建立了基于最大完工时间和总成本的算法选择模型.利用仿真算例比较了2种算法在不同情况下的求解效果,并给出了算法的选择准则.仿真结果表明,该方法能为以云制造平台为调度主体的供应链制定合理的生产计划.
        A production planning method of supply chain based on cloud manufacturing platform was presented. The purposes of this method were to minimize the makespan,total service cost and total transportation cost. In order to effectively solve the presented model,a genetic algorithm and an improved genetic-annealing algorithm were designed. Meanwhile,a model for selecting the efficient algorithms was established based on the makespan and total cost. The results of two algorithms in different situations were compared by simulation example,and then a selection criteria of the algorithms was given. The simulation results shown that the proposed method can provide a reasonable production plan for the supply chain based on the cloud manufacturing platform.
引文
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