Last‐mile parcel delivery remains a major challenge in rural areas where unpaved roads, long travel distances, and sparse demand limit the efficiency of truck‐based logistics. This study evaluates the use of cargo drones as a replacement for trucks, focusing on the design of a statewide delivery network supported by multimodal hubs. It introduces an empirical multiobjective (EMO) procedure for hub placement that accounts for population density, airport proximity, and infrastructure readiness. The EMO procedure is compared to a classic single‐objective (CSO) approach that minimizes network distance, using data from North Dakota to demonstrate the models. Results show that while the CSO model minimizes travel distance, it selects hubs in low‐demand areas with limited infrastructure. In contrast, the EMO procedure increases population coverage almost ninefold, improves service equity, and enables integration with air freight systems. Cost analysis reveals that drones become more competitive than trucks as demand decreases, particularly in rural regions. Sensitivity analysis highlights strategies to achieve cost parity, including scaling drone operator batch sizes and reducing capital and insurance costs. This research provides a practical, data‐driven framework for statewide drone logistics planning and demonstrates how rural states can benefit from advanced air mobility solutions.
Raj Bridgelall (Thu,) studied this question.