A multi-objective evolutionary approach to aircraft landing scheduling problems
Ke Tang, Zai Wang, Xianbin Cao, Jun Zhang · 2008
Scheduling aircraft landings has been a complex and challenging problem in air traffic control for long time. In this paper, we propose to solve the aircraft landing scheduling problem (ALSP) using multi-objective evolutionary algorithms (MOEAs). Specifically, we consider simultaneously minimizing the total scheduled time of arrival and the total cost, and formulate the ALSP as a 2-objective optimization problem. A MOEA named Multi-Objective Neighborhood Search Differential Evolution (MONSDE) is applied to solve the 2-objective ALSP. Besides, a ranking scheme named non-dominated average ranking is also proposed to determine the optimal landing sequence. Advantages of our approaches are demonstrated on two example scenarios.