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Advances of operations research in air transportation in the intelligence age

Author

Listed:
  • Wen, Xin
  • Choi, Tsan-Ming
  • Ma, Hoi-Lam
  • Sun, Xuting

Abstract

The constant growth in the demand of air cargo and air passenger nowadays has imposed many new challenges to the operations and management in the aviation industry. Both the academia and the industry have devoted great efforts to coducting extensive research and developed many new operations research (OR) techniques to address complex aviation management issues. In response to the expansion of aviation networks and the growth of flight frequencies, researchers have attempted to combine emerging technologies, such as artificial intelligence (AI), with OR techniques to achieve better results. This paper reviews the literature of advanced OR in air transportation, introduces and summarises the papers featured in this special issue, identifies the research development trends, and provides future research directions for aviation management. The reviewed studies are divided into three areas: airline operations, aviation data analysis and decision-making, and aviation sustainable development. Airline operations research focuses on four aspects of airline scheduling, including flight scheduling, fleet assignment, aircraft maintenance routing, and crew scheduling. Aviation data analytics and decision-making research focuses on operational safety and efficiency, profitability, delays, and disruption management. Finally, aviation sustainable development focuses on the aspects of subsidy policies, environmental protection, and the application of emerging technologies in supporting the long-term development of the aviation industry. By reviewing and analyzing the related studies, we propose a list of future research directions.

Suggested Citation

  • Wen, Xin & Choi, Tsan-Ming & Ma, Hoi-Lam & Sun, Xuting, 2025. "Advances of operations research in air transportation in the intelligence age," Journal of Air Transport Management, Elsevier, vol. 122(C).
  • Handle: RePEc:eee:jaitra:v:122:y:2025:i:c:s096969972400156x
    DOI: 10.1016/j.jairtraman.2024.102691
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