Determination of the optimum number of unmanned air vehicles required for surveillance activities

The purpose of this thesis study is to calculate at least how many unmanned aerial vehicles (UAVs) should be used in region where an aerial observation activity will be carried out. Firstly, the energy consumption of a UAV while moving at a constant speed has been examined to do this calculation. The percent energy level that the UAV consumed per meter is roughly achieved. The length of the orbit on which a UAV will move is consider . It is estimated that what percentage of its energy will be consumed for the UAV to complete 1 turn in this orbit. If it is determined that 1 UAV cannot complete the specified orbit, the number of UAVs is increased until the completion of the orbit of each UAV used. In this thesis study, vehicle routing problem was used to calculate the UAV orbits. For the solution of vehicle routing problem, the method of genetic algorithm which is the metasesistical optimization method was used. The developed algorithm was run in Matlab. Parameters of genetic algorithm method were changed. These are population numbers and crossover rates. By changing the number of population and crossover rate, the lowest UAV enough to carry out observation activities in an area was tried to be obtained with the shortest possible UAV orbits.