Affiliation:
1. College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China
2. Yonsei Frontier Laboratory Yonsei University Seoul South Korea
3. Faculty of Engineering Ocean University of China Qingdao China
4. Faculty of Mechanical Engineering Opole University of Technology opole voivodeship Poland
5. School of Vehicle and Mobility Tsinghua University Suzhou Automotive Research Institute Suzhou Jiangsu China
Abstract
AbstractThe 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.
Publisher
Institution of Engineering and Technology (IET)
Subject
Law,Mechanical Engineering,General Environmental Science,Transportation
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