北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2018, Vol. 41 ›› Issue (2): 15-20.doi: 10.13190/j.jbupt.2017-113

• 论文 • 上一篇    下一篇

基于云制造平台的供应链生产计划方法

孔继利1, 曹文颖2, 杨福兴1   

  1. 1. 北京邮电大学 自动化学院, 北京 100876;
    2. 北京航空航天大学 经济管理学院, 北京 100191
  • 收稿日期:2017-06-19 出版日期:2018-04-28 发布日期:2018-03-17
  • 作者简介:孔继利(1982-),男,副教授,硕士生导师,E-mail:kongjili1026@bupt.edu.cn.
  • 基金资助:
    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)

Production Planning Method of Supply Chain Based on Cloud Manufacturing Platform

KONG Ji-li1, CAO Wen-ying2, YANG Fu-xing1   

  1. 1. Automation School, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. School of Economics and Management, Beihang University, Beijing 100191, China
  • Received:2017-06-19 Online:2018-04-28 Published:2018-03-17

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.

关键词: 云制造平台, 供应链, 生产计划, 改进遗传退火算法

Abstract: 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.

Key words: cloud manufacturing platform, supply chain, production plan, improved genetic-annealing algorithm

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