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Multiobjective Gate Assignment Model Considering Carbon Emissions

Author

Listed:
  • Yixuan Shan

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Yuwei Shao

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Qi Yuan

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Yu Jiang

    (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

It has been a main concern for governments to reduce the carbon emission of the aviation industry. The paper proposes a multiobjective gate assignment model that considers the carbon emission at the airport surface to facilitate environmental-friendly airport construction. Three objectives are considered in the model to reduce carbon emissions, including the proportion of flights assigned to the contact gate, aircraft taxiing fuel consumption, and gate assignment robustness. In order to achieve better performance on all objectives, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to obtain the optimal results. The operation data from a domestic airport is deployed to validate the model. The optimal results of the gate assignment model are compared with the original scheme. It indicates that the proposed model can effectively reduce carbon emissions. The study can provide a strategy for gate assignment to reduce carbon emissions and improve the management of the airport.

Suggested Citation

  • Yixuan Shan & Yuwei Shao & Qi Yuan & Yu Jiang, 2023. "Multiobjective Gate Assignment Model Considering Carbon Emissions," IJERPH, MDPI, vol. 20(5), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:3952-:d:1077578
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    References listed on IDEAS

    as
    1. Yin, Suwan & Han, Ke & Ochieng, Washington Yotto & Sanchez, Daniel Regueiro, 2022. "Joint apron-runway assignment for airport surface operations," Transportation Research Part B: Methodological, Elsevier, vol. 156(C), pages 76-100.
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