Data Analysis and Monte Carlo Simulation of Airport Check-In Process - MA, Nang Laik (Institutional Knowledge at Singapore Management University, 2011)
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.