The traditional P-median selecting location model of logistics is based on the statistical static model. These traditional mathematical models often don't consider topography, transport conditions, slop etc. The distance between two nodes is often assumed for the straight line in this model, so the analytical result usually can not be used as a warehouse in actual applied. So the paper isn't only takes a catena supermarket warehouse as an example and adopts the geographical information system (GIS) technology, spatial analysis methods and remote sensing images to establish warehouse selection model of logistics distribution, but also improves P-median selecting location model. At the same time, the most suitable warehouse location is determined by multi-standards. The method mainly includes three processes: building networks, handling remote sensing and overlapping networks to remote images. Since the networks' distance is used in the model, the analysis result is more science and more close to reality. And the method can reduce blindness of choosing the warehouse location in catena manage, the customer is given some information of assistance decision.
展开▼
