计算机集成制造系统 ›› 2014, Vol. 20 ›› Issue (5): 1228-.DOI: 10.13196/j.cims.2014.05.chenjiumei.1228.9.20140526

• 产品创新开发技术 • 上一篇    下一篇

两级定位—路径问题的路径重连变邻域搜索人工蜂群算法

陈久梅1,2,曾波1,2   

  1. 1.重庆工商大学电子商务及供应链系统重庆市重点实验室
    2.重庆工商大学商务策划学院
  • 出版日期:2014-05-30 发布日期:2014-06-12
  • 基金资助:
    国家自然科学基金资助项目(71101159,71271226);教育部人文社科青年基金资助项目(11YJC630273)。

Artificial bee colony algorithm with variable neighborhood search and path relinking for two-echelon location-routing problem

  • Online:2014-05-30 Published:2014-06-12
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71101159,71271226),and the Humanities and Social Science Youth Fundation of Ministry of Education,China(No.11YJC630273).

摘要: 为适应物流需求从少品种大批量到多品种少批量的转变,建立了两级定位—路径问题的数学模型,提出求解该问题的路径重连变邻域搜索人工蜂群算法,即在基本人工蜂群算法中嵌入近年来广泛应用于组合优化问题求解的两种启发式搜索策略——变邻域搜索和路径重连。采用Lingo求解小规模两级定位—路径问题;选取三组较大规模的两级定位—路径问题,分别采用基本人工蜂群算法、路径重连人工蜂群算法、变邻域搜索人工蜂群算法和路径重连变邻域搜索人工蜂群算法进行求解。结果表明,所建数学模型是正确的,所提算法不但能够取得更好的优化结果,而且具有更好的收敛性。

关键词: 两级定位&mdash, 路径问题, 人工蜂群算法, 路径重连, 变邻域搜索, 物流

Abstract: To adapt the transformation of logistics demand from few varieties with large batch to many varieties with small batch,a mathematical model of two-echelon location-routing problem was established,and the artificial bee colony algorithm with variable neighborhood search and path relinking was put forward to solve this model.LINGO was used to solve small scale two-echelon location-routing problem.Basic artificial bee colony algorithm,artificial bee colony algorithm with path relinking,artificial bee colony algorithm with variable neighborhood search,artificial bee colony algorithm with path relinking and variable neighborhood search were applied to solve three groups of larger scale two-echelon location-routing problem separately.The results showed that the proposed mathematical model was correct,and the proposed algorithm not only had better optimization results,but also had better convergence.

Key words: two-echelon location-routing problem, artificial bee colony algorithm, path relinking, variable neighborhood search, logistics

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