genetic-immune algorithm based on receding horizon for aircraft landing scheduling problems

Abstract:

Flight scheduling has been a complex and key task for the air traffic control (ATC), and aircraft landing scheduling (ALS) problem is one of the core issues. ALS is a NP-hard problem with a large scale and multi-constraints characteristics. Thus, in order to solve the flight landing problem effectively and rationally, a flight landing scheduling algorithm based on receding horizon and genetic-immune algorithm (RHC_HGIA) is proposed. RHC_HGIA solves the problem of flight landing by two aspects mainly, one is that selecting the flights that are waiting to land and need to be optimized based on the receding horizon length and size which have been set; on the other hand, optimizing The selected flights which are waiting to land by using genetic-immune algorithm and determining actual landing time of them. the flights that have been optimized form a new flight landing sequence, selecting the flights from the sequence that the actual landing time of them in the field within a given time range to land. Then resetting receding horizon length and re-selecting the flights to be optimized until all pending landings have landed so far. In this paper, simulation is conducted in the airport control simulation system on the base of an airport of 20 flights to be landing of one day. Simulation results show that, RHC_HGIA algorithm can solve ALS problem preferably, and comparing with traditional flights landing scheduling algorithm(FCFS), the extra costs of flight is reduced much more.