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Green and Low Carbon Gate Assignment Based on Genetic-Tabu Search Algorithm
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Yu-xiu CHEN1, 2, Li-yan QUAN1, 2, Jian YU3, Li-chao ZHANG4
Science Technology and Engineering | 2025, 25(1) : 410 - 415
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Science Technology and Engineering | 2025, 25(1): 410-415
• Papers·Aeronautics and Astronautics •
Green and Low Carbon Gate Assignment Based on Genetic-Tabu Search Algorithm
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Yu-xiu CHEN1, 2, Li-yan QUAN1, 2, Jian YU3, Li-chao ZHANG4
Affiliations
  • 1. College of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
  • 2. Research Center for Environment and Sustainable Development of the China Civil Aviation, Tianjin 300300, China
  • 3. Civil Aviation Management Institute of China, Beijing 100102, China
  • 4. Jiamusi Dongjiao Airport, Jiamusi 154000, China
Published: 2025-01-08 doi: 10.12404/j.issn.1671-1815.2308081
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With the increasingly serious problem of climate change, green and low-carbon operations have become an important principle for the sustainable development of the air transportation industry. Taking a single runway transport airport as the research object and green and low-carbon and passenger walking distance as the optimization objective, a green and low-carbon gate assignment model under multiple scenarios was constructed, and a genetic-tabu search combined optimization algorithm was designed to solve it. Finally, a transport airport in northeast China was taken as an example for simulation experiment. The experimental results are shown as follows. In the optimal assignment scheme, if considering green and low-carbon, the fuel consumption can be reduced by 3.1%, the taxiing distance of the aircraft by 3.1%, HC emission by 4.2%, CO emission by 3.6%, NOX emission by 3.1%, and CO2 emission by 3.1% comparatively. But passenger walking distance can be increased by 5.3% at the same time. If considering green and low-carbon as well as the interests of the passengers, the fuel consumption can be decreased by 2.1%, the taxiing distance of the aircraft by 2.2%, HC emission by 3.8%, CO emission by 2.7%, NOX emission by 2.0%, CO2 emission by 2.1%, and passenger walking distance by 2.1% comparatively. Thus, it is possible to strike a balance between green and low-carbon development and the interests of travelers.

gate assignment  /  green and low-carbon  /  passenger walking distance  /  genetic algorithm  /  tabu search algorithm
Yu-xiu CHEN, Li-yan QUAN, Jian YU, Li-chao ZHANG. Green and Low Carbon Gate Assignment Based on Genetic-Tabu Search Algorithm[J]. Science Technology and Engineering, 2025 , 25 (1) : 410 -415 . DOI: 10.12404/j.issn.1671-1815.2308081
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doi: 10.12404/j.issn.1671-1815.2308081
  • Receive Date：2023-10-17
  • Online Date：2025-07-29
  • Published：2025-01-08
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History
  • Received：2023-10-17
  • Revised：2024-07-19
Funding
Affiliations
    1. College of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
    2. Research Center for Environment and Sustainable Development of the China Civil Aviation, Tianjin 300300, China
    3. Civil Aviation Management Institute of China, Beijing 100102, China
    4. Jiamusi Dongjiao Airport, Jiamusi 154000, China
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