Enhancing Airport Efficiency by Simulating Passenger Waiting Times

Year 2024, Volume: 1 Issue: 1, 47 - 51, 02.08.2024

Mehmet Taha Uyar , Güney Gürsel

Abstract

In this study, a detailed simulation model of airport operations was developed using the SimPy library to analyze passenger waiting times at security, check-in, and boarding points. QuickPassenger was evaluated to reflect realistic scenarios of different passenger profiles, such as tourists and those requiring special assistance (e.g. disabled, pregnant). The primary objective was to evaluate how resource management and passenger prioritization affected overall waiting times. Simulation results showed that optimizing resource allocation significantly reduced wait times, especially at security checkpoints, which are often the bottlenecks. This study provides valuable information to airport managers to increase operational efficiency and improve passenger experiences through strategic resource planning and prioritization.

Keywords

Simulation, Airport Operations, Passenger Flow, Waiting Times, Resource Management

References

• Akpur, A. (2024). Adapting to the skies: evolution of qualified personnel in airline operations amid technological advancements. Worldwide Hospitality and Tourism Themes, 16(3), 13-24.
• Anagnostopoulou, A., Tolikas, D., Spyrou, E., Akac, A., & Kappatos, V. (2024). The Analysis and AI Simulation of Passenger Flows in an Airport Terminal: A Decision-Making Tool. Sustainability, 16(3), 1346
• Avogadro, N., Birolini, S., Redondi, R., & Deforza, P. (2024). Assessing airport ground access interventions: An integrated approach combining mode choice modeling and microscopic traffic simulation. Transport Policy, 148, 154-167.
• Gadzhimusieva, D., Gorelova, A., Beigbeder, S. M., & Lledó, G. L. (2024). Enhancing Accessibility in Academic Buildings: A Discrete Event Simulation Approach for Robotic Assistance. IEEE Access.
• Ofoegbu, W. C., & Felix, O. O. (2024). OPERATIONS MANAGEMENT AND ITS CRUCIAL ROLE TO STABILIZE THE NIGERIAN ECONOMY. GPH-International Journal of Business Management, 7(02), 46-58.
• Li, X., An, X., & Zhang, B. (2024). Minimizing passenger waiting time in the multi-route bus fleet allocation problem through distributionally robust optimization and reinforcement learning. Computers & Operations Research, 164, 106568.
• Liu, C., Chen, Y., Zhang, Y., Wang, H., Luo, Q., & Chen, L. (2024). Reliable and robust scheduling of airport operation resources by simulation optimization feedback and conflict resolution. Neurocomputing, 573, 127212.
• Liu, Y., Hu, M., Yin, J., Su, J., & Qiao, P. (2024). Adaptive airport taxiing rule management: Design, assessment, and configuration. Transportation Research Part C: Emerging Technologies, 163, 104652.
• Luo, M., Fricke, H., Desart, B., Zapata, S. R., & Schultz, M. (2024) High-Fidelity Digital Twin Applied Agent-Based Model for Supporting Predictable Airport Ground Operations. Available at SSRN 4806351.
• Ma, X., He, Z., Yang, P., Liao, X., & Liu, W. (2024). Agent-based modelling and simulation for life-cycle airport flight planning and scheduling. Journal of Simulation, 18(1), 15-28.
• Manataki, I. E., & Zografos, K. G. (2009). A generic system dynamics based tool for airport terminal performance analysis. Transportation Research Part C: Emerging Technologies, 17(4), 428-443.
• Oudani, M., Zkik, K., Belhadi, A., Kamble, S., Sebbar, A., & El Raoui, H. (2024). Organizational resilience of the airline industry using an Integrated epidemic and airline hub location model with traffic prediction. Annals of Operations Research, 1-26.
• Papatheodorou, A. (2021). A review of research into air transport and tourism: Launching the Annals of Tourism Research Curated Collection on Air Transport and Tourism. Annals of Tourism Research, 87, 103151.
• Scozzaro, G. (2024). Optimization of airport operations during access mode disruptions to improve passengers experience (Doctoral dissertation, Université de Toulouse).
• Xu, Y. (2024). Perspectives on Modelling Airline Integrated Scheduling Problem: a Review on State-of-the-Art Methodologies. Journal of the Air Transport Research Society, 100023