计算机应用 ›› 2010, Vol. 30 ›› Issue (9): 2279-2282.

• 人工智能 • 上一篇    下一篇

基于异类多种群蚁群算法的MC供应链分布式调度研究

张鹏1,林杰2,魏云霞3   

  1. 1. 同济大学经济与管理学院;西安理工大学
    2. 同济大学 经济与管理学院
    3. 陕西省银行学校
  • 收稿日期:2010-03-12 修回日期:2010-05-02 发布日期:2010-09-03 出版日期:2010-09-01
  • 通讯作者: 张鹏
  • 基金资助:
    国家863/CIMS主题资助项目;国家自然科学基金重点项目;新世纪优秀人才支持计划资助;上海市重点学科建设项目

MC supply chain distributed scheduling based on heterogeneous multiple ant colony algorithm

  • Received:2010-03-12 Revised:2010-05-02 Online:2010-09-03 Published:2010-09-01
  • Contact: Peng Zhang

摘要: 分析了目前大规模定制(MC)供应链调度现有调度方法的不足,针对MC供应链调度具有分布式和计算规模大的特点,提出了异类多种群蚁群算法,并设计了MC分布式调度优化的模型。异类多种群蚁群算法由多类不同特性蚁群构成,不同类型蚁群具有不同特质,并优势互补,彼此间具有潜在的合作性。将多个进行寻优的异类蚁群分散到供应链的不同计算节点上多个蚁群进行协同工作,蚁群间既独立也协作,充分发挥并行高效的特点,满足大规模定制供应链调度的要求。此模型算法可根据多订单特点,充分利用供应链上分布的计算资源,对调度规模大而且复杂的供应商选择及企业间合作时序进行寻优,确定优化调度方案。实验结果证明,该算法模型具有较好的有效性、稳定性和订单适应能力。

关键词: 大规模定制, 供应链调度, 蚁群算法, 异类多种群蚁群

Abstract: The deficiencies of the existing Mass Customization (MC) supply chain scheduling models were summarized. According to the characteristics of distributed scheduling and large scaled computing, a MC supply chain scheduling model was designed. Heterogeneous multiple ant colony algorithm was presented to achieve this scheduling model. This algorithm introduced more than one type of ant colony. All types of ant colonies with different pheromone updating mechanism and searching traits had mutual compensation of advantages as well as mutual competitive exclusion so that they can potentially cooperate smoothly. Collaborations among ant colonies distributed in different location of supply chain fully took the advantages of whole computing resources of supply chain, obtained fairly solving speed, and fulfilled scheduling requirements of multi-order including supplier selection and inter-enterprise scheduling. Finally practical manufacture case was used to prove the proposed algorithm model's validity, stability and order adaptability.

Key words: Mass Customization (MC), supply chain scheduling, ant colony algorithm, heterogeneous multiple ant colony

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