Terör ve suç faaliyetleriyle mücadele için geliştirilmiş genetik algoritma kullanarak verimli bir İHA yolu planlama yaklaşımı

Drones are a very popular type of aircraft that has seemingly taken over the world. Other widely used names for drones are Unmanned Aerial Vehicles (UAVs) and Remotely Piloted Aerial Systems (RPAS). Drones are being extensively consumed in today's world, not just by government authorities and law enforcement but also by commercial and private entities. However, the effectiveness of using drones as a long-term strategy for counter-terrorism, counter-insurgency, controlling criminal activities remain unclear. This research aims to examine the perceived effectiveness of using drones in combating terrorism and criminal activities. Moreover, presenting new path planning techniques based on tree seed algorithm and genetic algorithm (TSAGA). The presented approach applied to find the best path for the drone when used to visit more than one location or goal. The proposed TSAGA assist the drones to find the minimum path which lead to Energy saving and solving the energy problem in the drones which is one of the main problems in drone technology. Then, the obtained results by the TSAGA compared with classical GA and show that the proposed approach is best and better in both energy saving and execution time.