Genetic algorithm with adaptive immigrants for dynamic flight path planning

Dynamic flight path planning is an important part of UAV mission planning, and it turns out to be a dynamic optimization problem. In this paper, a dynamic flight path planning model is built up. We propose an adaptive immigrant scheme genetic algorithm for this path planning problem. This algorithm could combine the random immigrant scheme and elitism-based immigrant scheme adaptively according to the number of feasible candidate solutions in the current population, and improve the diversity and convergence of GAs. Simulation studies show that the algorithm has good performance in finding near-optimal, obstacles-free paths in dynamically changing environments.