The Application of Brain Drain Optimization Algorithm on Static Drone Placement Problem

With the advancement of technology, the desire to use more robots and computers instead of humans has also grown. One of the robots that can be used in lots of situations is a drone. Drones can be used to control or monitor some targets but finding the optimal position for them to fly is a big problem that is in the group of NP-hard problems. In this paper, we tried to solve the static drone placement problem with a recently-proposed swarm intelligence algorithm called BRADO which is derived from the migration of humans between countries. The results of our experiments show that BRADO has worked well in solving the problem. In our tests, we used static drones and targets deployed in a squared search space and our goal is to find the optimal position for the drones in a way that all of the targets will be covered. The results of our proposed solution were better than some other famous meta-heuristic algorithms. The outcome of our work shows that BRADO works well with the static drone placement problem.