Multi-UAV Path Planning with Genetic Algorithm.

With the continuous evolution of communication technology, unmanned aerial vehicles (UAVs) are considered pivotal in 6G communications. As the number of tasks steadily increases, simultaneous path planning for multiple UAVs has emerged as an important research topic. The multi-path planning problem for UAVs is essentially a typical instance of the multiple traveling salesman problem (MTSP). Since the MTSP problem is NP-hard, the effect of using heuristic optimization algorithms will be significantly better than traditional optimization methods. To optimize the information collection process, we employ the Kmeans clustering method to generate relay nodes. Subsequently, a multi-UAV path planning model is constructed, and a genetic algorithm (GA) is employed to find the optimal solution. Finally, the effectiveness of the proposed GA in tackling the MTSP problem is validated through comprehensive experiments under diverse scenarios.