一种基于区域路径优化的混合聚类方法

A hybrid clustering method based on zoning route optimization

针对局部优化物流路径时效率低下,无法在全局上实现实际需求应用的问题,建立了一种基于区域划分的物流路径优化模型ZROM(Zoning-routing optimization model),并提出了一种改进Apriori混合聚类分析的KM-A方法求解该模型。该方法利用K-Means聚类分析来划分物流区域,在区域内部利用改进的基于最小代价容忍度的频繁序列模式挖掘算法对路径进行优化。实验分析表明,KM-A方法在覆盖节点网络中目标节点数量相同的情况下可以有效提升物流路径运送的效率,结果合理且具有高度可靠性。

Aiming at the problem of low efficiency local logistics path to hardly optimize the actual globle demand, a logistics route optimization model based on region partition ZROM （Zoning-routing optimiza- tion model） is established, and an improved apriori hybrid clustering algorithm KM-A is proposed to solve the model, in which K-Means clustering analysis routing optimization is performed within the area by the is adopted to classify the logistics areas, and the frequent sequential pattern mining algorithm based on the minimum cost tolerance. Experimental analyses show that KM-A method will improve the efficien- cy of logistics routing with the same number target nodes in the coverage network, which is reasonableand reliable.