Continuous Approximation Approach to Determine the Optimal Service Area for a Drone Port in Urban Air Logistics

The aviation sector employs innovative technical involvements, applications, and operational practices. As a result, unmanned aerial vehicles that are remotely piloted from a ground station usher in the next phase of both passenger and freight transportation. This study is focused on freight transportation using drones. Although many studies in the past have focused on various drone delivery configurations, this study finds a critical research gap when evaluating the drone port location problem for a set of centralized ports where service is shared among multiple demand generators. Addressing the research gap, this study adapts the approach of continuous approximation (CA) in model development to find the optimum area allocated to a centralized drone port in an urban area. Findings indicate that the drone service range is a limiting factor for the optimal service area of the drone port. Furthermore, it was revealed that the optimal service area and the minimum total delivery operation cost have a low sensitivity to factors such as the shape of the service area, demand density and travel cost per unit distance.