Locating charging stations and routing drones for efficient automated stocktaking
研究在仓库中部署无人机进行库存盘点时，如何规划无人机飞行路线并确定充电站位置，以解决电池容量限制问题，并开发了一种自适应大邻域搜索启发式算法来高效求解。
Drones have received growing attention in logistics recently. One possible application is deploying drones for auditing inventory in warehouses. With the use of drones, warehouses are able to increase inventory record accuracy and decrease labor costs. In this research, we introduce the stocktaking drone routing problem (STDRP), which consists of routing a fleet of drones through a warehouse for stocktaking purposes as well as deciding on the location of charging stations on the warehouse floor, which is necessary due to the limited battery capacity of the drones. Subsequently, we develop an adaptive large neighbourhood search-based heuristic (ALNS) with novel solution encoding and decoding approaches to solve the STDRP. In a numerical study, we show that ALNS can solve realistic instances in reasonable time. We also derive recommendations regarding the ideal size of the drone fleet, the charging infrastructure, and battery capacity. Finally, we investigate the interplay between the storage assignment policy (such as the popular ABC rule) and stocktaking efficiency using drones.