Weighted clustering of spatial pattern for optimal logistics hub deployment

Optimal logistics hub deployment is a strategic challenge in logistics planning and management. Selecting a proper location for the logistics hub could be significantly impacted by long-term geospatial characteristics of logistics operations including spatial distribution of target customers, convenience of traffic access and operational cost. This paper describes a method using clustering of weighted spatial patterns to find optimal locations for logistics hubs deployment. The underlying concept of this method is that an optimal location of the hub could be determined by logistics operation patterns mined from logistical spatial and temporal data. A logistics spatial pattern can be produced by spatial association rules mining and clustering. The spatial patterns weighted by characteristics of logistics operations are then be clustered to generate the final hub location. In this study, the method is validated with a real data sets of pick-up and delivery business. The experimental results demonstrated that the method was able to generate an optimal location for logistics hub deployment with reduced travel distance to frequent customers' locations.