Exploring Mixed-Grid Environments for Drone-Based Last-Mile Logistics Optimization

In recent years, drone-based delivery systems have gained significant attention for last-mile logistics in various domains. This study focuses on optimizing drone deliveries in mixed-grid environments, which combine urban and rural areas. The objective is to minimize the sum of distances between the delivery locations and the drone’s depot. By selecting the optimal depot placement, we aim to improve factors such as expected delivery time, energy consumption, and environmental impacts. To address this optimization problem, we conducted a comprehensive comparison of several state-of-the-art algorithms specifically designed for computing the drone placement in mixed-grid environments. Our evaluation utilized synthetic and quasi-real data and two distinct scenarios were considered: the full-grid scenario, and the partial-grid scenario. Through empirical analyses, we demonstrate the effectiveness of the proposed algorithms and provide valuable insights into their trade-offs in terms of performance and time complexity.