基于数据挖掘的快递末端配送点选址优化方法
Optimization method for location selection of express terminal delivery points based on data mining
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作者信息
- 1. 安徽水利水电职业技术学院基础部,安徽合肥 231603
- 折叠
摘要
基于末端配送点位以及配送路径优化问题,提出了电商企业联合配送站点三级选址-路径优化的两层规划模型,并通过基于数据挖掘的聚类和改进遗传混合启发式算法对模型求解,以提升精准度.结果表明,研究算法寻优性能优异,且计算误差值为0.087,平均运行时间为30.911 s;同时,通过MATLAB仿真实验,成功生成了基于末端配送的最优路径规划,验证了模型的可行性.有效解决了快递末端配送网络的选址-路径规划问题,在物流配送服务上效率更高,成本更低.
Abstract
Based on the optimization problem of terminal distribution points and distribution paths,a two-level programming model for three-level site selection and path optimization of joint distribution sites in e-commerce enterprises is proposed.The model is solved through clustering based on data mining and improved genetic hybrid heuristic algorithms to improve accuracy.The results show that the research algorithm has excellent optimization performance,with a calculation error value of 0.087 and an average running time of 30.911 seconds.Meanwhile,through MATLAB simulation experiments,the optimal path planning based on end delivery was successfully generated,verifying the feasibility of the model.The research has effectively solved the location path planning problem of the express delivery terminal distribution network,resulting in higher efficiency and lower costs in logistics delivery services.
关键词
末端配送/选址优化/双层规划模型/3E-LRP/K-meansKey words
terminal delivery/site optimization/bilevel programming model/3E-LRP/K-means引用本文复制引用
基金项目
2020年度安徽省自然科学重点项目(KJ2020A1041)
2022年度安徽省自然科学重点项目(2022AH052304)
出版年
2024
NETL
NSTL
万方数据