基于图论的聚类算法在订单分批问题中的应用  

Application of Graph Theory Based Clustering Algorithm in Order Batching Problem

作　　者：吴天行[1] 郭键[1] 

机构地区：[1]北京物资学院,北京101149

出　　处：《物流技术》2017年第8期112-116,共5页Logistics Technology

基　　金：北京市属高等学校青年拔尖人才培育计划项目(CIT&TCD201504052);北京物资学院青年运河学者资助项目;北京物资学院国家级科研项目培训基金项目

摘　　要：首先阐述了传统的基于相似巷道的订单分批模型的原理,然后根据图论和聚类分析的相关原理,建立了基于图论的聚类算法订单分批模型,最后通过一个实际的算例,以最小拣选路径为目标函数,分别对未分批订单、基于巷道相似性分批的订单和基于图论的聚类算法分批的订单结果进行了比较,从而论证了该算法的有效性。In this paper, we first elaborated on the working principle of the order batching model based on the traditional channel similarity principle, then according to the graph theory and clustering analysis, built the order batching model using the graph theory based clustering algorithm, and at the end, through an empirical numerical example, compared the order batching result based on channel similarity and based on the clustering algorithm, thus demonstrating the validity of the algorithm developed in this paper.

关 键 词：拣选作业 订单分批 图论 聚类分析 

分 类 号：F224[经济管理—国民经济] F252.21