Flight path planning based on improved genetic algorithm

Path planning, which was one of the key technologies increasing the survival probability of the military aircraft, could get an optimal path in large-scale real environment. So it was important to choose a suitable algorithm. In recent years, genetic algorithm (GA) had been successfully applied to path planning problems for unmanned aerial vehicle (UAV) systems, including single-vehicle system and multi-vehicle systems. This paper designed a new encoding method by using array-encoding, and improved the mutation operator with combination of reconstruction operator and disturbance operator. And it developed adaptive genetic algorithm for optimal path planning, which determined the optimal path between the nodes with respect to a set of cost factors and constraints. By the example simulation, it gets reasonable result which indicated that the new algorithm could satisfy the compute efficiency and the precision of solution. It was easier to realize and improved its practicability.