Abstract: Based on the Pareto optimal conception,an Improved nondominated sorting genetic algorithm II (NSGA-II) seeking non-inferior solution set of multi-objective optimization (MO) problems is proposed, while the heuristic crossover operator based on nearest-neighborhood, the improved mutation operator and the filtering of non-inferior solutions are focused and discussed. The algorithm proposed is applied to a two-objective optimization of scheduling of arrival aircrafts at an airport with multiple runways, where both the sum of all the delays squared and the fuel cost of all the aircrafts were required to be minimized. After the simulation experiment, the optimal solutions are analyzed and compared with the best solutions founded by some existing algorithms. The research result demonstrates that improved NSGA-II possesses a good application foreground for multi-objective optimization of scheduling arrival aircrafts at an airport with multiple runways.