Airport slot allocation with low-carbon consideration

Abstract

Continuously increasing carbon emissions pose new challenges to the civil aviation industry. Although new techniques to reduce emissions are being developed, the aviation industry still calls for research on advanced management practices. Airport slot allocation in air traffic flow management aims to reduce flight delays by rescheduling flights. This study extends previous research by proposing a low-carbon air traffic management model that considers flight carbon emissions during airport slot allocation. The model is formulated as a nonlinear integer programming. A flight-based variable neighborhood search algorithm is developed to solve the model. The algorithm is extended by operating flights in different slots within an airport network. Computational experiments on real-world data show that the algorithm can generate a near-optima solution within a short amount of time. A case study based on the solutions indicates that the model can effectively reduce carbon emissions by 26.3%, while simultaneously maintaining delays at a comparable level. These results provide insights into future practices for the civil aviation industry.