计算机集成制造系统 ›› 2016, Vol. 22 ›› Issue (第3期): 806-812.DOI: 10.13196/j.cims.2016.03.025

• 产品创新开发技术 • 上一篇    下一篇

完全自产情境下的推拉组合式生产链协同规划

吴继兰,邵志芳+,韩景倜,李丹   

  1. 上海财经大学信息管理与工程学院
  • 出版日期:2016-03-31 发布日期:2016-03-31
  • 基金资助:
    国家自然科学基金资助项目(71271126,71171126);教育部博士点专项科研基金资助项目(20120078110002);上海市自然科学基金资助项目(12ZR1409800);国家863计划资助项目(2014AA052501)。

Collaborative planning of push and pull production chain under self-producing situation

  • Online:2016-03-31 Published:2016-03-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71271126,71171126),the Research Fund of the Doctoral Program of Ministry of Education,China(No.20120078110002),the Shanghai Natural Science Foundation,China(No.12ZR1409800),and the National High Tech.R&D Program,China(No.2014AA052501).

摘要: 为研究推式策略、拉式策略、推拉组合式生产策略下的生产链协同规划问题,构建了完全自产情境下的生产链多厂规划数学模型。分析了完全自产情境下的规划模型,并探究了初始化方法对模型求解结果的影响。采用某液晶面板生产企业的实际数据,通过粒子群算法对模型进行求解,并与线性规划法求得的结果进行比较,验证了智能算法的有效性。根据可外购情境和完全自产情境下的模型结果比较分析,认为完全自产情境下的模型可计算订单的最大允诺量、识别产能瓶颈,对现实企业生产管理具有重要意义。

关键词: 生产链协同规划, 推拉组合式生产策略, 粒子群算法, 液晶面板

Abstract: To research the production chain collaborative planning problem under the push strategy,pull strategy,push and pull combined production strategy,the production chain multi-site planning mathematical model under completely self-produced context was constructed.The planning model under completely self-produced context was analyzed,and the influence of initialization method on  model solution was discussed.Meanwhile,the model was solved through particle swarm optimization algorithm based on the actual data of a LCD panel production enterprise,and the validity of intelligent algorithm was proved according the comparison with linear programming method.According to the comparison analysis between outsourcing situation and completely self-produced context model,the maximum order to promise could be calculated by “completely self-produced situation” model,and the capacity bottlenecks could be recognized,whichhad important significance for the enterprise production management.

Key words: production chain co-planning, push and pull production strategy, particle swarm optimization algorithm, liquid crystal display panel

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