An evolutionary multi-objective approach for Network-wide Conflict-free Flight Trajectories Planning

Under the demand of strategic Air Traffic Flow Management (ATFM) and the concept of Trajectory Based Operations (TBO), studies on the Network-wide Conflict-free Flight Trajectories Planning (NCFTP) has been motivated with the purpose of allocating all the 4D trajectories to realize a conflict-free airspace. However, the introduction of accurate 4D trajectories increases the problem complexity, and the collaborative decision-making philosophy calls for economical and fair plans for airlines. In this paper, therefore, we formulate a multi-objective 4D trajectories planning problem to minimize flight cost and maximize fairness on the premise of a conflict-free trajectory planning. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is adopted to solve this large-scale constrained optimization problem. Moreover, a specific heuristic operator is hybridized in the algorithm to rapidly de-conflict 4D trajectories and accelerate the optimization process. Empirical studies using the real air traffic data in China show that the proposed evolutionary multi-objective approach is effective to solve the NCFTP problem. And the solutions achieved provide elaborate decision support under TBO environment for decision-makers.