Joint Optimisation of Taxiing Mode and Gate Assignment for Close Parallel Runways Based on Genetic Algorithms

For close parallel runway airports equipped with end-around taxiways (EAT), the joint optimisation of taxiing mode selection and gate assignment is essential to improving operational efficiency and safety. This study proposes a joint optimisation model based on a genetic algorithm, aiming to minimise ground run-time for both arrivals and departures while maximising the utilisation of contact stands equipped with passenger boarding bridges (bridge rate). A refined taxiing time calculation method is introduced to capture the operational differences between runway crossing and EAT detour scenarios, explicitly incorporating runway incursion risk. Simulation results based on Shanghai Hongqiao International Airport show that the proposed model reduces total average flight delays by 17.75%, shortens the average barrier-free taxiing time for arrival flights by 10.07%, and improves the overall bridge usage rate by 12.22%. The model offers a practical decision-support tool for airport operators to balance efficiency, safety, and resource utilisation.