@inproceedings{5f77f2041b334c0da0534f650513811b,
title = "A large neighbourhood search approach to airline schedule disruption recovery problem",
abstract = "The occurrence of unplanned aircraft shortages and disruption of flight schedules during the day-to-day operations of airlines is inevitable. When equipment failure causes unsafe flight, the aircraft will be grounded or temporarily delayed when the weather shuts down the airport or the required flight crew is unavailable. Real-time decisions must be made to reduce revenue loss, passenger inconvenience and operating costs by reallocating available aircraft and cancelling or delaying flights. A large neighbourhood search algorithm is used in this research to construct a feasible and efficient solution to the airline schedule disruption recovery problem. We aim to reduce the aircraft turn-around times, including total delay time, the number of flight adjustments and the number of flights delayed for more than one hour, as an objective function. Ten real-life cases are solved, and the proposed approach yields an approximate 50% improvement in solution quality. ",
keywords = "Airline recovery, Fleet assignment, Large neighbourhood search, Passenger itineraries",
author = "Ng, {Kam K.H.} and Keung, {K. L.} and Lee, {C. K.M.} and Chow, {Y. T.}",
note = "Funding Information: The research is supported by Interdisciplinary Funding Information: Division of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong SAR and Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR and College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong SAR, China. Our gratitude is also extended to the Research Committee and the Interdisciplinary Division of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University for support of the project (BE3V). Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2020",
month = dec,
day = "14",
doi = "10.1109/IEEM45057.2020.9309768",
language = "English",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
publisher = "IEEE Computer Society",
pages = "600--604",
booktitle = "IEEE International Conference on Industrial Engineering and Engineering Management 2020",
address = "United States",
}