| 摘要: |
| 目的 针对快递包装重复利用率低、回收难的现象，建立有效的快递包装回收网络，提高快递包装的回收效率。方法 文中通过改进的K-均值聚类与集合覆盖模型相结合的方法对回收点选址进行研究。首先利用改进的K-均值聚类对快递点进行聚类分析，求解快递网点的平均差异度，并通过选定原则得到初始聚类中心，减少迭代的次数，将最终聚类中心作为候选回收点。再利用集合覆盖模型进行优化，在候选回收点的基础上选出回收点，为充分利用现有物流资源，选取最近的快递网点作为回收点。结果 以最少的回收点数量覆盖了所有的快递网点，降低了网络的回收成本，提高了快递包装回收效率。结论 通过2种方法的结合选择出了合适的快递网点作为回收点。利用SPSS和Matlab软件对SY市的回收点选址进行了实例分析，验证了该方法是有效的。 |
| 关键词: 快递包装 回收点 改进的K-均值聚类 集合覆盖模型 |
| DOI：10.19554/j.cnki.1001-3563.2020.11.029 |
| 分类号:TB485.3；F252 |
| 基金项目:辽宁省社科规划基金（L18AGL005） |
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| Location Selection of Recycling Points in Express Packaging Recycling Network |
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ZHOU Xiao-ye, REN Gui-bin, MA Xiao-yun, ZHU Mei-lin, ZHONG Yu
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School of Management, Shenyang University of Technology, Shenyang 110870, China
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| Abstract: |
| The work aims to establish an effective express packaging recycling network and select reasonable locations regarding the phenomena of low recycling rate of express packaging and difficult recycling, in order to reduce the cost of the network and improve the recycling benefits. The improved K-means clustering and set covering model were combined to study the location of the recycling point. First, the improved K-means clustering was used to perform cluster analysis on the express outlets. The average difference of the express outlets was solved and the initial cluster center was obtained through the selection principle. The number of iterations was reduced, and the final cluster center was used as the candidate recycling point. Then, the set covering model was used for optimization, and the recycling points were selected on the basis of the candidate recycling points. In order to make full use of the existing logistics resources, the nearest express outlet was selected as the recycling point. All express outlets were covered by the least number of recycling points, reducing the network’s recycling cost and improves the efficiency of express packaging recycling. Through the combination of these two methods, a suitable express outlet is selected as the recycling point. SPSS and Matlab software are used to analyze the location of the SY city-wide recycling point to prove that the proposed method is effective. |
| Key words: express packaging recycling point improved K-means clustering set covering model |
