An improved non-dominated sorting genetic algorithm Ⅱ （NSGA-Ⅱ） for solving the large-scale optimization problem of trajectory planning in the strategic stage is designed. Under the framework of the classic NSGA-Ⅱ， an adaptive crossover operator and an adaptive mutation operator are used to accelerate the convergence speed of the algorithm and improve the quality of the solution， and an evaluation index to measure the pros and cons of the Pareto solution set is given. Considering the introduction of large-scale four-dimensional trajectories inevitably increases the complexity of the problem， this paper proposes an effective strategic conflict resolution model， which aims to minimize the number of potential conflicts and the cost of conflict resolution. Using 1 472 flights during peak hours of China’s air-route network for example verification， the proposed algorithm is compared with the classic NSGA-Ⅱ algorithm and MOEA/D. The experimental results show that the improved NSGA-Ⅱ algorithm has a better optimization effect， can effectively resolve the conflicts between aircraft and produce less trajectory amendment costs.