Regional-Scale Multimodal Service Optimization for Innovative Air Mobility Using MILP

By 2050, 90% of European travelers are expected to complete door-to-door journeys within four hours, a target that would require a substantial expansion of transport infrastructure, particularly in rural areas, which account for 19.2% of the population. Innovative Air Mobility (IAM), which can enhance regional connectivity while relying on limited ground infrastructure, represents a promising solution to this challenge. This paper proposes an IAM service optimization model for integrating IAM into regional multimodal transport networks. The problem is formulated as a mixed-integer linear programming (MILP) model. To address computational tractability, a vertiport connection sparsification technique is introduced to reduce model complexity. The sparsified model is solved using CPLEX, and a case study is used to validate its performance. The results indicate that the sparsification technique reduces model complexity to 18.5% of the original formulation and, on average, performs better than a heuristic-based approach.