Joint gate-runway scheduling considering carbon emissions, airport noise and ground-air coordination

With the rapid increase in air traffic, the scheduling optimization of one single resource is difficult to meet the needs of airport surface operation. Thus, we propose a new joint scheduling model of airport gate and runway with three different objectives, i.e., service quality (minimizing the number of flights assigned to aprons), operation efficiency (maximizing the ground-air coordination) and environmental impact (minimizing the carbon emissions during the whole process of aircraft ground operation and airport noise disturbance). Then, we apply the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) with an improved population initialization method to solve the model. Finally, we perform a case study based on Guangzhou Baiyun International Airport (CAN). The results show a negative correlation between operational efficiency and environmental impact. The optimized scheme can at most reduce 48 flights assigned to aprons, make all flights ground-air coordinated, or reduce 12.07t carbon emissions and 0.55 dB noise level at the runway end. Furthermore, we compare the median and minimum Pareto schemes to the original scheme. It is found that the model proposed in this paper optimizes not only the original assignment scheme on three objectives, but also the gate assignment robustness, runway usage balance, and other benefits.