Çoklu kısıtlamalar içeren insansız hava araçları ile görev planlama probleminde zaman planlaması ve hedef görevlendirmesi.

In the recent years, unmanned aerial vehicles (UAVs) have started to be utilized as the first choice for high risk and long duration tasks, because UAVs are cheaper; they are hard to be noticed and they can perform long duration missions. Furthermore, the utilization of UAVs ensures to reduce the risk to the human life. Examples of this kind of missions includes signal collection, surveillance and reconnaissance and combat support missions. It is valuable to develop a fully autonomous UAV fleet to perform these kinds of tasks when it is needed, because this kind of missions usually start at unexpected times. Other problems which is in the set of high risk and long duration tasks are multiple constraint UAV scheduling, and target assignment problem. In this problem, a fleet of UAVs are supposed to traverse a set of target areas within a limited area. The targets are only available within certain time windows and need to be traversed promptly. Moreover, for some large target areas multiple UAVs are needed to perform the task. The objective of this problem is to find a complete scheduling and UAV-target assignment that minimizes the total fuel consumption of the UAVs. This problem is a highly critical real time problem and needs to be solved almost in real-time. Therefore, methods doing exhaustive search are infeasible. Most of the methods in the literature, try to solve this problem by evolutionary approaches. In this thesis, we developed an algorithmic method to solve this problem. This method uses divide and conquer method to solve this problem. In this way, the problem is transformed into a combination of multiple small problems. We designed a method to convert these small problems into transportation problems. Each transportation problem is solved with simplex algorithm. The method proposed is compared with various methods and has been shown to provide fast, acceptably optimal and reliable results.M.S. - Master of Scienc