基于GIS技术和加权kNN算法的实时揽件调度方法  

Real-Time Express Pick-Up SchedulingMethod Based on GIS Technology andWeighted kNNAlgorithm

作　　者：应毅[1] 任凯[2] 刘亚军[3] YING Yi;REN Kai;LIU Yajun(College of Computer Science and Technology,Sanjiang University,Nanjing 210012,China;Jinling College,Nanjing University,Nanjing 210089,China;School of Computer Science and Engineering,Southeast University,Nanjing 210096,China)

机构地区：[1]三江学院计算机科学与工程学院,南京210012 [2]南京大学金陵学院,南京210089 [3]东南大学计算机科学与工程学院,南京210096

出　　处：《计算机工程与应用》2020年第21期248-252,共5页Computer Engineering and Applications

基　　金：国家自然科学基金青年基金(No.61502206);江苏省高等学校自然科学研究面上项目(No.17KJB520033);江苏高校“青蓝工程”(苏教师[2018]12号)。

摘　　要：在物流末端的配送服务中,实时揽件调度研究尚处于空白。基于GIS技术、Web技术和移动开发技术,构建了针对“最后一公里”配送的智能物流信息系统。在此系统框架内,改进加权kNN分类算法实现快递人员的实时揽件调度。通过在菜鸟驿站某网点配送活动中的应用,表明智能物流信息系统能有效提升物流网点的服务质量,实时揽件调度方法也对解决实际问题效果显著。In the end delivery service of logistics,the research on real-time express pick-up scheduling is still in blank.Based on GIS technology,Web technology and mobile development technology,an intelligent logistics information system for“last kilometer”distribution is constructed.In the framework of this system,weighted kNN classification algorithm is improved to make real-time express pick-up scheduling for delivery man in reality.Through the application of distribution activities on rookie post station(a website to provide end delivery service),the intelligent logistics information system mentioned above can effectively improve the service quality of the logistics network.Meanwhile,the real-time express pick-up scheduling algorithm proposed in this paper has a significant effect on solving practical problems.

关 键 词：智能物流信息系统 实时揽件调度 ARCGIS 加权kNN算法 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]