Efficient Approaches for Drone-Assisted Vehicle Parcel Delivery Routing Problems in IoT Logistics Ensuring Optimized Energy Consumption

Recently, the drone-assisted vehicle routing problem in IoT logistics has become a prominent area of investigation within the academic community. It is particularly relevant to IoTs in transportation and logistics, notably for last-mile delivery. Drones launch from the designated stops to serve customers, then land at hubs to join another vehicle for further deliveries, all while adhering to constraints such as flying range and capacity limitations. Integrating vehicle and drone routing presents unique challenges because it requires synchronization for both vehicle and drone scheduling to optimize the overall completion time or delivery system cost. In this paper, we introduce the Drone-Vehicle Hybrid Scheduling Problem (VDHS) aimed at optimizing delivery costs. Subsequently, we develop two efficient algorithms for solving the VDHS problem. Our routing and scheduling algorithm enables a fleet of drones, transported by a swarm of vehicles, to deliver multiple parcels simultaneously to customers at various locations, with the objective of minimizing delivery costs. Through extensive experimentation on realistically generated instances, the experimental results demonstrate the effective computational performance of the proposed algorithms. Additionally, we conduct sensitivity analysis on a critical factor influencing the total solution cost.