摘要
针对共同配送策略下带时间窗的选址-路径问题进行了研究,考虑客户点时间-空间分布,构建了以总成本最小为目标函数的选址-路径优化模型,设计了基于k-means客户点时空聚类算法,并运用粒子群算法求解车辆路径。最后构造算例,验证了模型和算法能较好地实现客户点配送划分、确定共同配送中心选址、最优车辆派遣数计算,可为共同配送模式优化研究提供新的求解思路,为构建共同配送联盟提供决策支持,探索城市共同配送模式优化路径。
For joint distribution,the location-allocation problem with time windows is studied.Considering customer spatio-temporal distribution,an optimization model with total cost minimization as optimization goal.The customer Spatio-temporal clustering algorism based on k-means method is designed,and Particle Swarm Optimization(PSO)is applied to obtain the distribution vehicle paths.Finally,the example is generated to verify the effectiveness of the model and algorism,which enables to solve the problems of customer division,joint distribution centre location,and distribution vehicle allocation.This study can bring new thinking to joint distribution research and provide decision support to build joint distribution alliance,exploring the optimization path of urban joint distribution.
作者
梁辰
徐扬
LIANG Chen;XU Yang(School of Information and Business Management,Dalian Neusoft University of Information,Dalian 116023,China)
出处
《物流工程与管理》
2021年第8期84-87,共4页
Logistics Engineering and Management
关键词
共同配送
时空聚类
选址-分配问题
时间窗
joint distribution
spatio-temporal clustering
location-allocation problem
time windows
