摘要
With the increasing use of unmanned aerial vehicles (UAVs) in logistics, the expansion of fleets and the employment of diverse UAV types for particular orders has become a prevalent trend. This adds complexity to route and schedule planning for operators. To address these challenges, this study develops a daily delivery routing and scheduling model for a mixed-type UAV fleet using network flow techniques and mathematical programming. The objective of this model is to minimize operating costs while considering crucial factors such as UAV flight operations and battery limitations. Furthermore, this study considers two categories of policy costs: penalties for delaying and for aborting orders. Given the complexity of this NP-hard problem, a Lagrangian relaxation method is used to develop a solution algorithm. A case study confirms the model and algorithm's effectiveness in helping operators plan efficient delivery routes and schedules.