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Aircraft-sequencing problem (ASP) is a major issue in air traffic control operations and it is also an NP-hard problem with large-scale and multi-constraint, thus it is hard to find optimal solution efficiently. This paper proposes a hybrid algorithm by means of integrating bee evolutionary genetic algorithm with modified clustering method (named BEGA-CM) for solving ASP. In details, clustering method is suitable to deal with distribution of arrival time window, moreover, we newly define the relative and absolute position in aircraft permutation according to its distribution of cluster, which can help us to construct new crossover and mutation operator and efficiently reduce infeasible permutation and improve convergence speed. Experiments show the hybrid algorithm is able to obtain an optimal landing sequence and landing time rapidly and effectively.