Title :
Research on location methods of RDC in high-density logistics network points
Author :
Du, Xinjian ; Cai, Shanshan ; Yang, Haoxiong ; He, Mingke
Author_Institution :
Bus. Sch., Beijing Technol. & Bus. Univ., Beijing, China
Abstract :
Many large enterprises are establishing high-density logistics network points to improve customer satisfaction. From the point of logistics efficiency increases, it is an effective method. But it also results in repeated construction. To avoid increasing logistics cost and wasting social resources, a method based on Self-Organizing Feature Map and Baumol-Wolfe model is used. Compared to general location methods, its innovative point is the combined use of cluster analysis, and its result can be easily got by using Matlab and successive-approximation algorithm. In the end, a practical calculation example is used to analyze the feasibility and superiority of this method.
Keywords :
customer satisfaction; logistics; self-organising feature maps; Baumol-Wolfe model; Matlab; RDC; cluster analysis; customer satisfaction; general location methods; high-density logistics network points; location methods; logistics cost; self-organizing feature map; successive-approximation algorithm; wasting social resources; Algorithm design and analysis; Clustering algorithms; Concrete; Construction industry; Cost function; Customer satisfaction; Logistics; Mathematical model; Production facilities; Unsupervised learning; Baumol-Wolfe Model; High-density Logistics Network; Location method; Self-organizing Feature Map;
Conference_Titel :
Logistics Systems and Intelligent Management, 2010 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-7331-1
DOI :
10.1109/ICLSIM.2010.5461071
