Abstract
Front Distribution Centre (FDC) is a new terminal warehouse which is closer to customer, and its location selection is crucial for e-commerce and customer time satisfaction. We introduce in this paper a joint distribution function of demand based on time and space and design a staged clustering algorithm to obtain the candidate FDCs. Using an intelligent algorithm based on NSGA-Ⅱ (Non-dominated Sorting Genetic Algorithm II), the location selection problem is formulated as a bi-objective programming model to minimise the total cost and maximise customer time satisfaction. Our results indicate the demand spatio-temporal joint distribution matter and perform better than traditional spatial model. Furthermore, compared with traditional k-means clustering, the solving method based on staged clustering and NSGA-II is more effective and can help reduce total cost by up to 38.84% and improve customer time satisfaction by up to 36.22%