Abstract
To improve the airport’s operation, we use Monte Carlo simulation to determine the optimal number of check-in counters required for a single flight with 200 scheduled passengers in a 2-h check-in period. Our analysis of the passenger arrival pattern supported that the inter-arrival time can be approximated using an exponential distribution. By using the Monte Carlo Simulation model with increasing number of check-in counters, we were able to conclude that three check-in counters were optimal to satisfy the service level requirement that at least 90% of the passengers must be served within 10 min upon arrival at the check-in queue. In additional, we further extend our analysis to cater for different passenger loads from 50 to 500 and determine the linear relationship between the number of counters required and passenger load. Finally, we use the daily flight schedule, to get the check-in counters requirement for daily operations.
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Acknowledgment
This paper is part of the consultancy work done by the faculty members for one of the busiest airport in the region. The client would like to remain anonymous and we appreciate the company for the support and knowledge sharing.
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Laik, M.N., Choy, M. (2019). Resource Planning at the Airport. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-01174-1_65
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DOI: https://doi.org/10.1007/978-3-030-01174-1_65
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