Bilevel spatial–temporal aircraft taxiing optimization considering carbon emissions

Air transportation pollution is mainly caused by aircraft carbon emissions. One of the key methods for reducing aircraft carbon emissions is to optimize the taxiing route on the airport surface. In view of this, a bilevel spatial–temporal taxiing optimization model considering carbon emissions is proposed in this paper. A bilevel programming method is deployed in the model to minimize the carbon emissions, taxiing waiting time, and conflicts of aircraft, which not only facilitates environmentally friendly airport establishment but also improve airport operation efficiency. Particularly, the influence of taxiing conflicts and turning action are considered when calculating the carbon emissions in the paper, which provides a more effective subjective for the model. An iterative neighborhood search algorithm is proposed to solve the model. The operation data of Baiyun Airport in China are utilized to validate the model. The results indicate that, compared with the first-come first-serve (FCFS), the proposed model reduces the total carbon emissions of aircraft by 814 kg on the premise of no taxiing conflict or 2% of the total. Compared with tabu search, it can reduce carbon emissions by 375 kg. This study can provide a more environmentally friendly taxiing strategy for aircraft and reduce carbon emissions.