Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (2): 214-221.DOI: 10.3778/j.issn.1002-8331.1607-0253

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Strategic supply chain integration research based on genetic algorithm

HAN Xiaolong, LI Shang, YANG Quanye   

  1. Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
  • Online:2018-01-15 Published:2018-01-31


韩晓龙,李  上,杨全业   

  1. 上海海事大学 科学研究院物流研究中心,上海 201306

Abstract: In the study of a strategic supply chain, the paper considers the three main stages of the supply chain, procurement, production, distribution and their interaction, different customer demands, facilities matching relationship, supplier priority and existing supply chain design model limitations. A Mixed Integer Nonlinear Programming(MINLP) model is established. An Adaptive Genetic Algorithm(AGA) is used to solve the constraint of the large-scale mixed integer nonlinear programming model, and the optimization is carried out by the Adaptive Genetic Algorithm(AGA). Finally, the experimental results show that the proposed mixed integer nonlinear programming model can effectively solve the problem of supply chain collaborative optimization in strategic supply chain design, and can get a better supply chain design.

Key words: strategic supply chain design, mixed integer nonlinear programming, supplier priority, adaptive genetic algorithm

摘要: 在战略供应链研究中,考虑供应链的三个主要阶段,采购、生产、配送和它们之间的相互作用,不同客户需求,设施配对关系,供应商优先权以及现有供应链设计模型的局限性,建立了混合整数非线性规划(MINLP)模型。为有效地解决这种大规模混合整数非线性规划模型的约束,采用自适应遗传算法(AGA)对该模型进行求解优化。实验结果表明,所提混合整数非线性规划模型能够有效解决战略供应链设计中的供应链协同优化问题,并能得到较优的供应链设计方案。

关键词: 战略供应链设计模型, 混合整数非线性规划, 优先供应商, 自适应遗传算法