摘要
针对多中心联合配送的车辆路径问题,构建了一种既考虑需求点时间窗口相近性又考虑地理空间邻近性的聚类算法,首先设计了时空距离计算方法,然后运用DBSCAN进行时空聚类,并将聚类结果应用于GIS路径求解中。最后,构造算例分析验证了模型和算法的有效性和可靠性,为快速有效地解决此类问题提供了一种新的思路。
Aimed at vehicle routing problem in joint distribution among multi centers,a clustering algorithm was developed with consideration both in time window adjacency and geographical spatial proximity.Time-space distance was first calculated and then DBSCAN clustering was applied to the time-space distribution of demand points,path solving was last carried out based on GIS.Finally,an example was tested to verify the effectiveness and reliability of the proposed model and algorithm,demonstrating a new thought for this kind of problems.
作者
梁辰
周峻旭
LIANG Chen;ZHOU Junxu(Dalian Neusoft University of Information,Dalian 116023,China)
出处
《物流科技》
2021年第9期45-47,共3页
Logistics Sci-Tech
关键词
时空聚类
多配送中心
联合配送
车辆路径问题
GIS
time-space clustering
multi-depot
joint distribution
vehicle routing problem
GIS
