Airport terminal building capacity evaluation using queuing system

Khalid Abdulaziz Alnowibet, The American University in Cairo (AUC)
Awad Khireldin
Mohamed Abdelawwad
Ali Wagdy Mohamed, The American University in Cairo (AUC)


Queues or waiting lines are a natural occurrence in the everyday lives of consumers and the process of every business. Being customers' first point of contact with the business, a customer’s experience in the queue becomes a determining factor of their first impression of the business. Queuing provides the cornerstone of efficiency to businesses as they assist employees and managers in tracking, prioritising, and ensuring the delivery of services and transactions. Inefficiencies in queues are undesired as they can result in substantial losses to a business, such as bad reputation and loss of customers due to balking or reneging behaviour. Previous research has shown that the application of queuing theory enables businesses to analyse their queuing system and the trends of demand for their services. This allows the business to effectively identify measures to improve their queuing system and serve demand at the desired level of service. In this paper, where it examined Cairo International Airport (CAI)’s existing departure queue system and benchmarked it against the optimum wait time suggested in the International Air Transport Association’s (IATA) Level of Service (LoS) concept. The application of Kendall-Lee’s Notation is applied to describe the existing queuing system of the airport. It also suggested areas of improvement after the analysis and recommended that the CAI focus on improving service time for its Check-in, Security, and Boarding process. Although the Immigration process has met IATA’s recommended optimal wait time, training could be provided to employees to enable them to progressively work towards a better service time and prepare for the future higher traffic volume. The team has also suggested for CAI to introduce autonomous technology for the departure process and software which analyses passenger flow and projects a forecast value based on the airport growth trends.