Abstract: This paper proposes three steps to solve the severe en-route airspace congestion in China. First, it analyzes the coupling effect caused by flight flows between neighbor airspace units, and then presents an en-route capacity model under coupling constraints between neighbor airspace units. Second, in order to reflect the different arrival time limitations of different flights,it defines the flight delay cost functions and rerouting cost functions. Third, the paper developes a 0-1 integer programming model for collaborative multiple en-route slot resource allocation which integrates the rerouting and delay tactics. In addition,a heuristic algorithm based on the Hungarian algorithm is developed to compute the model. Finally, a series of simulation experiments are performed using the operational data of the Beijing-Guangzhou route in the range of the Central South China Air Traffic Control Center. Numerical results show that the resource rationing under collaborative decision reduceds the average delay time of congested flights by more than 30% and it reduces the average delay cost of congested flights by more than 40% as compared with those under non collaborative decision making. The results also demonstrate that, under both collaborative and non collaborative strategy, the proposed models may reduce the average delay costs by more than 20% as compared with those under the first schedule first service (FSFS) rule.

Key words: air traffic control, resource allocation, coupling constraint, en-route capacity, collaborative rerouting, Hungary algorithm