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计算机工程 ›› 2011, Vol. 37 ›› Issue (7): 196-198. doi: 10.3969/j.issn.1000-3428.2011.07.066

• 人工智能及识别技术 • 上一篇    下一篇

基于多种群蚁群算法的大规模定制供应链调度

张 鹏1,2,林 杰1,刘思伟3   

  1. (1. 同济大学经济与管理学院,上海 200092;2. 西安理工大学经济与管理学院,西安 710054; 3. 内蒙古兰太实业股份有限公司,内蒙古 阿拉善 750336)
  • 出版日期:2011-04-05 发布日期:2011-03-31
  • 作者简介:张 鹏(1975-),男,讲师、硕士,主研方向:系统仿真与建模,管理信息系统;林 杰,教授、博士;刘思伟,助理工 程师
  • 基金资助:
    国家自然科学基金资助重点项目(70531020);国家“863”计划基金资助项目(2007AA04Z151);新世纪优秀人才支持计划基金资助项目(NCET-06-0377);上海市重点学科建设基金资助项目(B310)

Mass Customization Supply Chain Schedule Based on Multiple Ant Colony Algorithm

ZHANG Peng  1,2, LIN Jie  1, LIU Si-wei  3   

  1. (1. School of Economics and Management, Tongji University, Shanghai 200092, China; 2. School of Economics and Management, Xi’an University of Technology, Xi’an 710054, China; 3. Inner Mongolia Lantai Industrial Co., Ltd., Alashan 750336, China)
  • Online:2011-04-05 Published:2011-03-31

摘要: 针对大规模定制供应链调度具有分布式和计算规模大的特点,引入多种群蚁群算法,设计分布式调度优化的模型,将多个进行寻优的蚁群分散到供应链的不同计算节点上。蚁群间既独立也协作、可发挥并行高效的特点,能满足大规模定制供应链调度的要求。根据多订单特点,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。实验证明,该算法具有较好的有效性、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, 多种群蚁群

Abstract: Deficiencies of existing Mass Customization(MC) supply chain schedule models are summarized. According to the characteristics of distributed schedule and large scaled computing, a MC supply chain schedule model is designed. Multiple ant colony algorithm is introduced to achieve this scheduling model. Collaborations among ant colonies distributed in different location of supply chain fully takes the advantages of whole computing resources of supply chain, obtained fairly solving speed, and fulfilled schedule requirements of multi-order including supplier selection and inter-enterprise schedule. Practical manufacture instance is used to prove the algorithm’s validity, stability and order adaptability.

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

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