A conflict avoidance approach based on memetic algorithm under 4D-Trajectory operation concept

Conflict avoidance plays a crucial role in guaranteeing the airspace safety. The current approaches mostly focusing on short-term which eliminate conflicts via local adjustment cannot provide global solution. Recently, the long-term conflict avoidance approach under the 4D-Trajectory (4DT) operation environment, is proposed to give solutions in a global view. However, with consideration of China air route network and thousands of flights plan, the problem is a large-scale combinatorial optimization problem with complex constraints which is hard to deal with. In this work, we present a strategic conflict avoidance approach based on memetic algorithm with a specially designed local search operator and an effective local search frequency strategy to improve the solution quality. Further, a fast genetic algorithm (GA) is adopted as the global optimization method. Empirical studies using real data of China air route network and daily flight plans show that our approach outperformed the existing approaches, the genetic algorithm based approach and the cooperative coevolution based approach.