Evolutionary dynamic optimisation of airport security lane schedules
Reducing costs whilst maintaining passenger satisfaction is an important problem for airports. One area this can be applied is the security lane checks at the airport. However, reducing costs through reducing lane openings typically increases queue length and hence passenger dissatisfaction. This paper demonstrates that evolutionary methods can be used to optimise airport security lane schedules such that passenger dissatisfaction and staffing costs can be minimised. However, it is shown that these schedules typically over-fit the forecasts of passenger arrivals at security such that in actuality significant passenger delays can occur with deviations from the forecast. Consequently, this paper further demonstrates that dynamic evolutionary re-optimisation of these schedules can significantly mitigate this over-fitting problem with much reduced passenger delays.
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Citation : Chitty, D., Gongora, M. and Yang, S. (2016) Evolutionary dynamic optimisation of airport security lane schedules. Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence
Research Group : Centre for Computational Intelligence
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes