Multiobjective Scheduling of Logistics UAVs Based on Simulated Annealing. This study focuses on the issue of logistics Unmanned Aerial Vehicle (UAV) distribution in urban environment, and an automatic delivery system to support the delivery of packages. It can effectively integrate existing facilities and be easily deployed. There is a scheduling problem in this system with multiple UAVs and multiple flights. We manage to optimize the two objectives of customer satisfaction and total completion time. The scheduling problem is formulated to a Mixed Integer Linear Programming (MILP), and we propose a multiple objectives decisionmaking method. A special encoding method suitable for the small scale problem is presented, and Simulated Annealing (SA) algorithm framework is used to generate the approximate optimal solution for this problem. In experiments, we calibrate the important parameter and analyze the robustness of the algorithm. The experimental results show that the proposed algorithm is suitable for this problem.

Control of a Novel Parcel Delivery System Consisting of a UAV and a Public Train A parcel delivery system with a unmanned aerial vehicle (UAV) and a public train is presented, where the train moves naturally as it is and the UAV can depart the train to deliver parcels. The UAV can travel with the train and replace its battery on the roof. An optimization problem is formulated to minimize the total delivery time and two algorithms are proposed. The exact algorithm gives the optimal schedule, but it is not scalable. The developed suboptimal algorithm is computationally efficient and achieves close performance to that of the exact algorithm. Realistic simulations are conducted to evaluate the proposed algorithms and they are compared with existing schemes.