Drone-based hybrid charging for multiple sensors: A distributionally robust optimization approach

The drone-based charging is emerging as a promising way to supply electricity to sensors that keep the Internet of Things working. One-to-one and one-to-many charging strategies can both be adopted. In this background, how to dispatch drones and decide the charging strategy becomes an important problem. In this paper, we first investigate the electricity consumption uncertainty during drone travel, and then develop a distributionally robust hover location and routing optimization model with hybrid charging strategies. After that, we transform the established model into a tractable mixed-integer linear programming model based on dual theory. In order to solve it, we introduce a pre-screening process based on greedy algorithm to select the candidate hover locations. Finally, we conduct extensive numerical experiments and sensitive analysis to verify the efficacy and advantages of the proposed method. We find that the optimized charging strategies and drone dispatching schemes can vary with different sensor distribution patterns. Valuable managerial insights are also provided for drone-based hybrid charging in practice.