Abstract: A new method of arrival sequencing and scheduling is proposed in this paper based on the multi-objective Imperialist competitive algorithm. This method can simultaneously consider different demands of air traffic control, airports, airlines, and the public, therefore balancing traffic demands and arrival management. The evaluation indicators of the arrival sequencing and scheduling are firstly combed and simplified, drawing on the research achievements in the field of machine scheduling, followed by the construction of a multi-objective arrival sequencing and scheduling model by combining the operating constraints. A Multi-Objective Imperialist Competitive Algorithm (MOICA) is then presented by introducing the non-dominated sorting strategy, and performance indexes are also provided to evaluate the pros and cons of Pareto solutions. Finally, a set of benchmark instances and the actual operation data of Changsha Huanghua International Airport are used to implement case simulation and verification, and comparison is made with the commonly used multi-objective algorithms such as NSGA-II or MOSA. The compared results exhibit a dominant position of the proposed MOICA with more uniform distribution, better convergence, and higher quality of the solution set. The proposed algorithm is also more efficient. Additionally, the proposed method can effectively realize the arrival sequencing and scheduling for the real case. Even when the simulation is performed at 1.8 times of the standard interval, the total delay time, total flight time, and maximum flight time are reduced by 41.2%, 11.4%, and 8.6%, respectively, relative to the actual operation.

Key words: air traffic management, approach management, multi-objective optimization, Imperialist competitive algorithm, point merge system