Carbon policy and its impact on optimizing large-scale green networks for long-term fuel consumption: A unified...

Transportation network optimization is crucial for the growth and sustainability of airline operations and stakeholders, where the corresponding sustainable hub-and-spoke (HS) structure design is the core yet tough task. However, the evolving demands for carbon peaking and neutrality have still not been addressed thoroughly, especially considering the emerging long-term fuel consumption demand. Thus, this study introduces a novel stochastic optimization framework that incorporates a proposed fuel-driven queue mechanism to meet the long-term carbon policy objectives. In particular, a comprehensive stochastic optimization model for reshaping the green hub-and-spoke airline network is proposed, taking into account system costs, multi-pollution emissions, and user satisfaction. Additionally, an instantaneous state-based approach is formulated to address a multi-slot long-term issue. A fuel-driven queue mechanism is utilized to characterize ton-kilometer fuel consumption. Also, a theoretical proof gives the stability analysis of the fuel-driven queue mechanism. Comprehensive simulations with typical national-level datasets are conducted. Results demonstrate that the proposed approach can effectively reduce 1.17 % fuel consumption and improve the running efficiency of 65.42 %. Additionally, it reduces transportation system costs, improves passenger satisfaction, and decreases aviation emissions simultaneously. Last, the proposed approach can be used to support the achievement of carbon policies and the transformation of the green transportation network.