Evaluation Analysis of the Resilience of the Air Transportation Network (Case Study: Domestic Passenger Flights in Iran)

Document Type : Original Article

Authors
1 Ph.D., Student, Management Faculty, Islamic Azad University Science and Research branch, Tehran, Iran.
2 Professor, Management Faculty, Tehran University, Tehran, Iran.
3 Professor,Faculty of Industrial Engineering‌, Science and Industry University, Tehran, Iran.
4 Assistant Professor, Management Faculty, Islamic Azad University, Central Unit, Tehran, Iran.
Abstract
Air transportation has always been of interest to national managers and planners due to its positive features, including high speed, safety, and large capacity. However, various constraints affect the efficiency of this system. In this research, the resilience of the air transportation network is examined. Constraints are divided into two categories: natural events and sabotage events. In this study, data from domestic flights in Iran were used to analyze the resilience of the air transportation network. For this purpose, the number of serviced flights was considered as an indicator of network performance, and the cascade failure diagram method was used to analyze resilience. The results show that in the most pessimistic scenario, with the removal of three airports, network performance drops below 10%, as indicated by the cascade failure diagram. Additionally, the ideal scenario of network performance decline was examined, and the results show that in this scenario, with the removal of 90% of airports, network performance remains above 45%. Based on the conducted analysis, the biggest problem in Iran's air network is the excessive concentration of flights in a few specific and high-demand airports, which greatly affects network resilience in case of any issues occurring for them.
Keywords

- Bombelli, A., Santos, B. F., & Tavasszy, L. (2020). Analysis of the air cargo transport network using a complex network theory perspective. Transportation Research Part E: Logistics and Transportation Review, 138, 101959.
-­Cai, Q., Alam, S., & Duong, V. (2020). On robustness paradox in air traffic networks. IEEE Transactions on Network Science and Engineering, 7(4), 3087-3099.
 -Chan, H., & Akoglu, L. (2016). Optimizing network robustness by edge rewiring: a general framework. Data Mining and Knowledge Discovery, 30(5), 1395-1425.
 - Cumelles, J., Lordan, O., & Sallan, J. M. (2021). Cascading failures in airport networks. Journal of Air Transport Management, 92, 102026.
 - Du, W. B., Zhou, X. L., Lordan, O., Wang, Z., Zhao, C., & Zhu, Y. B. (2016). Analysis of the Chinese Airline Network as multi-layer networks. Transportation Research Part E: Logistics and Transportation Review, 89, 108-116.
 - Faramondi, L., Setola, R., Panzieri, S., Pascucci, F., & Oliva, G. (2018). Finding critical nodes in infrastructure networks. International Journal of Critical Infrastructure Protection, 20, 3-15.
 -­Guo, J., Li, H., & Yang, Z. (2023, a). Robustness Analysis for China’s Airport Network Based on Multi-Layer Temporal Complex Network Model. In International Conference on Transportation and Development, 14-24.
 - Guo, J., Yang, Z., Zhong, Q., Sun, X., & Wang, Y. (2023, b). A novel resilience analysis methodology for airport networks system from the perspective of different epidemic prevention and control policy responses. PLoS One, 18(2), e0281950.
 - Guo, J., Zhu, X., Liu, C., & Ge, S. (2021). Resilience modeling method of airport network affected by global public health events. Mathematical Problems in Engineering, 2021, 1-13.
- Hossain, M., Alam, S., Rees, T., & Abbass, H. (2013). Australian airport network robustness analysis: a complex network approach. In Proceeding of the 36th Australasian Transport Research Forum, Brisbane, Australia.
 - Janić, M. (2022). Analysis and modelling of airport resilience, robustness, and vulnerability: impact of COVID-19 pandemic disease. The Aeronautical Journal, 2022, 1-30.
 - Li, S., Zhou, Y., Kundu, T., & Zhang, F. (2021). Impact of entry restriction policies on international air transport connectivity during COVID-19 pandemic. Transportation Research Part E: Logistics and Transportation Review, 152, 102411.
 - Lordan, O., Sallan, J. M., Escorihuela, N., & Gonzalez-Prieto, D. (2016). Robustness of airline route networks. Physica A: Statistical Mechanics and its Applications, 445, 18-26.
 -­Lordan, O., Sallan, J. M., Simo, P., & Gonzalez-Prieto, D. (2014). Robustness of the air transport network. Transportation Research Part E: Logistics and Transportation Review, 68, 155-163.
 -­Lordan, O., Sallan, J. M., Simo, P., & Gonzalez-Prieto, D. (2015). Robustness of airline alliance route networks. Communications in Nonlinear Science and Numerical Simulation, 22(1-3), 587-595.
 - Louzada, V. H., Daolio, F., Herrmann, H. J., & Tomassini, M. (2013). Smart rewiring for network robustness. Journal of Complex networks, 1(2), 150-159.
 -­Mahdavi, A. R., Mamdoohi, A., & Allahviranloo, M. (2021). Topology evaluation of Tehran subway network utilizing a bi-level mixed index for subway networks ranking. Amirkabir Journal of Civil Engineering, 52(12), 3003-3014.
-­Qian, B., & Zhang, N. (2022). Topology and Robustness of Weighted Air Transport Networks in Multi-Airport Region. Sustainability, 14(11), 6832.
 -­Soria, M., Lordan, O., & SALLAN, J. M. (2017). Heuristics of node selection criteria to assess robustness of world airport network. Chinese Journal of Aeronautics, 30(4), 1473-1480.
-­Sun, X., Gollnick, V., & Wandelt, S. (2017). Robustness analysis metrics for worldwide airport network: A comprehensive study. Chinese Journal of Aeronautics, 30(2), 500-512.
 -­Wang, Y., Zhan, J., Xinhua, X. U., Lishuai, L. I., Ping, C. H. E. N., & Hansen, M. (2019). Measuring the resilience of an airport network. Chinese Journal of Aeronautics, 32(12), 2694-2705.
 -­Ye, J., Ji, P., & Barthelemy, M. (2020). Scenarios for a post-COVID-19 world airline network. arXiv preprint arXiv:2007.02109.