Paper
14 June 2023 Flight schedule recovery based on the marginal benefits of airlines
Jun Bi, Junyu Shen, Fujun Wang, Bingjie Liang
Author Affiliations +
Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023); 1270828 (2023) https://doi.org/10.1117/12.2683857
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023), 2023, Chongqing, China
Abstract
With the continuous development of civil aviation, the airline's flight network and fleet size are increasing. In order to ensure that all flights of airlines can successfully perform flight missions and improve the overall operation efficiency of airlines, airlines need to invest more human and material resources to carry out the scheduling of flight schedules. At the same time, in some special cases, when some airports or flights are delayed due to irresistible factors, how to formulate a reasonable flight recovery schedule quickly and effectively is a key that affects the revenue and operation efficiency of airlines. Aiming at the flight delay scenarios under different circumstances, this paper proposes a flight schedule recovery method based on the existing operations of airlines, aiming at maximizing the marginal benefit, that is, the comparison between the marginal revenue of a flight and the marginal cost paid by the airline. This paper intends to improve the efficiency of flight recovery in the case of airline flight delays, and provide some reference for relevant enterprises.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Bi, Junyu Shen, Fujun Wang, and Bingjie Liang "Flight schedule recovery based on the marginal benefits of airlines", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023), 1270828 (14 June 2023); https://doi.org/10.1117/12.2683857
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KEYWORDS
Mathematical optimization

Adverse weather

Computer programming

Inspection

Industry

Stochastic processes

Transform theory

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