A multi-emission-driven efficient network design for green hub-and-spoke airline networks

The green hub-and-spoke airline network (GHSAN) is emerging as a dominant feature due to its excellent economic and environmental-friendly capabilities. However, environmental GHSAN designs still have some concerns, including single pollutant-domain oversimplification and lack of comprehensive network-level operation impacts. This paper proposes a multi-emission-driven efficient network design approach for GHSAN, utilizing a system, green, and user threefold optimization methodology. The approach includes a multi-objective optimization model and a two-layer solving method. The multi-objective optimization aims at minimizing multiple emissions, including carbon dioxide, carbonic oxide hydrocarbon, and nitric oxide, while also considering transportation system costs and journey user costs. A two-layer optimization algorithm is adopted to address different scales of optimization. Real-world results demonstrate that the proposed method mitigates environmental impact and user costs and increases overall airline density in airline networks. The proposed method can have a 16.29% reduction in green-fold (10 nodes) and a 12.06% decrease in user costs for the user-fold (10 nodes). As the number of nodes (15, 25, 50 nodes) and hubs (3, 4, 5, 6, 7 hubs) increase, the genetic algorithm (GA) proves to be more efficient and suitable in large-scale GHSAN. This work is further significant for the long-term and sustainable development of the future air transport industry. This paper proposes a multi-emission-driven efficient network design approach for the green hub-and-spoke network, utilizing a system, green, and user threefold optimization methodology. The system-fold mainly addresses transportation costs, the green-fold focuses on aviation emissions. And the user-fold considers passenger satisfaction, therefore converting the multi-hop journey user problem into user costs.image