Data Analysis and Monte Carlo Simulation of Airport Check-In Process
In a bid to increase airline business at one of the largest Asian airport, conflicting views of the availability of check-in counters drove the need for a more detailed analysis to aid decision making. We document here our attempt to determine the optimal number of check-in counters required for a single flight with 200 scheduled passengers in a 2-hour check-in period using Monte Carlo Simulation. Our analysis of the passenger arrival pattern supported that the inter-arrival time can be approximated to follow an exponential distribution. By testing 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 minutes upon arrival at the check-in queue. Any increase in the number of check-in counters will not improve service level significantly and instead it will result in wastage of check-in counters which would be under-utilized. In additional, we further extend our analysis to cater for different passenger loads from 50 to 550 and determine the linear relationship between the number of counters required and passenger load.
airport terminal management, check-in counter assignment, Monte Carlo Simulation, Spreadsheet modeling
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
MA, Nang Laik; CHEONG, Michelle Lee Fong; and CHOY, Junyu.
Data Analysis and Monte Carlo Simulation of Airport Check-In Process. (2011). Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1496
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