Warehouse Site Selection for Online Retailers in Inter-Connected Warehouse Networks

Abstract

Supply chain management aims at delivering goods in the shortest time at the lowest possible price while ensuring the best possible quality and is now vital to the success of the online retail business. Executing effective warehouse site selection has been one of the key challenges in the development of a successful supply chain system. While some effective strategies for warehouse site selection have been identified by the domain experts based on their experiences, the emergence of new ways of collecting fine-grained supply chain data has enabled a new paradigm for warehouse site selection. Indeed, in this paper, we provide a data-smart approach for addressing the connected capacitated warehouse location problem (CCWL), which searches for the minimum total transportation cost of the warehouse network including supplier-warehouses shipping cost, warehouse-customer delivering cost and the cost of warehouse-warehouse inter-transportation. Specifically, we first design a sales distribution prediction model and evaluate the importance of customer logistic service utilities on online market sales demand for online retailers. Then, we propose the E&M algorithm to optimize warehouse locations continuously with much less computation cost. Moreover, the computation cost is further reduced through delivery demand based Hierarchical Clustering which reduces the problem size by grouping delivering cities with close locations. Finally, we validate the proposed method on real-world e-Commerce supply chain data and the selection effect of new warehouses is evaluated in terms of sales improvement with faster delivery and more effective inventory management.