Single Runway Aircraft Landing Scheduling Using Simulated Annealing and Exact Timing Method One of the most challenging optimization problems in air traffic control is minimizing the deviation of aircraft arrival times from its target landing time. This can be achieved by efficiently allocating landing times and runways to the arriving aircraft. This problem is called the Aircraft Landing Problem (ALP). To address the ALP, this paper proposes a new approach which combines the Simulated Annealing (SA) algorithm with an exact timing method. The problem is solved in two stages: first, the optimal sequence is generated using the SA; in the second stage, the optimal landing time is determined using the exact timing method. The proposed approach is tested with ( 500 ) aircraft and a single runway using a wellknown benchmark dataset from the scientific literature. The obtained results demonstrated the ability of the proposed approach to generate promising and competitive results.

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.