The optimization of gate allocation and taxiway routing represents a critical challenge in enhancing airport ground operations performance. To simultaneously address these two closely coupled tasks, their interconnected processes are first modeled as flows in a spatiotemporal graph. On this basis, we develop a multi-objective optimization approach that accounts for both temporal and spatial factors across different operational aspects, effectively balancing the diverse needs of travelers, carriers, and airport authorities. To mitigate differences in scale and preference among various optimization objectives, min-max normalization combined with the linear weighting method is employed to transform the multi-objective problem into a single-objective one, which is solved by binary integer linear programming. Based on the actual operational data of Terminal 1 at Shanghai Pudong International Airport, three typical scenarios of different complexity are constructed for validation purposes. Performance comparisons with the state-of-the-art methods demonstrate the superiority of the proposed model in terms of various operational costs and parameter sensitivity. The integrated scheduling solution offers airport operators a reliable and efficient decision-making tool with practical applicability.
Du et al. (2026) studied this question.