Optimizing Drone Delivery Networks for Urban Air Mobility: A Comparative Analysis

This paper explores the application of the Capacitated Vehicle Routing Problem (CVRP) for drones in optimizing delivery networks, comparing three optimization methods: Mixed-Integer Linear Programming (MILP), Genetic Algorithm (GA), and Google OR-Tools. We assess the computational efficiency and effectiveness of these methods under different problem scales using selected locations from the Solomon dataset RC101. The results demonstrate that while exact routing methods provide optimal solutions for smaller scales, metaheuristic routing methods outperform in large-scale scenarios, offering a promising alternative for real-world drone logistics applications in Urban Air Mobility (UAM).