Evaluating the Impact of Vehicle Type on Mobile Warehouse Location Optimization and Operational Costs

The rapid growth of e-commerce has intensified the demand for efficient and sustainable last-mile home delivery (LMHD) solutions in urban settings. Many studies explore innovative last-mile home delivery solutions, but few have examined logistics setups that combine delivery vehicles with a mobile warehouse. In particular, there is a noticeable gap in research focusing on optimizing the location of a mobile warehouse within such integrated systems. This thesis investigates how the optimal location of a Mobile Warehouse (MW) is influenced when deployed alongside secondary delivery vehicles, such as Electric Cargo Bikes (E-CBs), Electric Vans and Diesel Vans. Distance as cost and Time as cost is used separately to evaluate optimised location of MW under such a setup. It further evaluates the cost-effectiveness of these MW-based delivery setups compared to traditional models. Using 38 demand points across the Swedish cities of Borlänge and Falun, simulations were performed employing p-median and k-center spatial optimization models. The results indicate that the overall optimal MW location remains consistent regardless of the type of second-level vehicle used, suggestinga degree of flexibility in vehicle pairing. While traditional diesel van delivery setup remains more cost-effective under current low-demand conditions, the analysis demonstrates that MW configurations become increasingly viable and economical as delivery density rises. The thesis supports the growing argument that MW-based LMHD systems, particularly when paired with cleaner and more agile vehicles like E-CBs, can significantly reduce operational costs and environmental impact in high-demand urban scenarios.