Nowadays, UAVs are actively used in military missions such as intelligence, reconnaissance and surveillance. The most important feature of UAVs is that they can be perform dangerous and risky missions since they are autonomous or remote controlled. UAVs are produced and used by many countries due to their abilities and the flexibility that they provide to various processes.

Military operations have a multi-objective nature due to their complexity. It is difficult to plan missions by considering a single objective. The main objective of UAV planning is to guarantee that UAVs return to the departure base or directed to another mission as soon as they complete the mission successfully. The routes of UAVs, which take off from different bases, are mainly determined by considering the position and duration of missions. While planning the route, a number of different objectives such as minimizing the travel time or travel distance, minimizing the fuel costs of UAVs or minimizing the deviations in the workload of the staff controlling the UAV can be defined.

In this study, the route planning is done by considering two objectives. The first objective is to minimize the total flight time of UAVs, whereas the second objective is to minimize deviations in the workload of the staff controlling the UAV. A Simulated Annealing algorithm in MATLAB is developed for this multi-objective problem. Problem specific neighborhood structures are designed for the developed algorithm. Next, the developed algorithm is tested by using problems produced to include different number of tasks. Results reveal that the proposed approach is capable of solving the defined problem in a reasonable time.