Simulating the emergency evacuation of the population during a crisis with a scenario-based approach

Document Type : Original Article

Authors

1 Assistant Prof. of Crisis Management Department, Non-Active Defense Faculty, Malek Ashtar University of Technology, Tehran, Iran.

2 Assistant Professor of Crisis Management Department, Non-Active Defense Faculty, Malek Ashtar University of Technology, Tehran, Iran.

3 Ph.D. Candidate of the Department of Crisis Management, Faculty of Non-Active Defense, Malek Ashtar University of Technology, Tehran, Iran.

Abstract

The purpose of this article is to model variables and scenarios affecting emergency evacuation during crises such as war and earthquake. The statistical population includes 160 specialists, academic staff and graduate students. The research method is descriptive-analytical. Random sampling method and Cochran's formula was used. Analysis has been done based on Wizard, Any Logic and Anp software. 8 scenarios with a maximum of two incompatible factors are considered for modeling in Any Logic. The more critical scenario obtained from the simulation was selected and the solutions were checked in the Anp software. Previous researches have not explained the simulated scenarios with the scientific method. We have used decision-making techniques and combined them with simulation to select solutions and scenarios. The evacuation time in the fifth scenario is longer than the other scenarios and we considered this scenario more critical. The results of Anp show that the criteria of adding doors and removing obstacles with weights of 0.287 and 0.262 have been ranked the highest. According to the normalized weight in the sub-criteria, in the criterion of time, the escape time in the corridors and stairs (with a weight of 0.65), in the cost, executive dimension (with a weight of 0.608), in the ability to execute, the ability to direct the operation. (with a weight of 0.8), in environmental effects, impact on the public (with a weight of 0.705) and in guarantee of traffic, the status of traffic management (with a weight of 0.756) have been ranked highest.

Keywords

Main Subjects

References

  •  

    • Alizadeh, A. , Vahidi Motlagh, v. & Nazmi, A. (2018). Scripting or planning based on Future think tank journalist,  11 (39): 61-90.
    • Bernardini, G. , Lovreglio, R. & Quagliarini, E. (2019). Proposing behavior-oriented strategies for earthquake emergency evacuation. Italy and Japan. Safety Science, 116 (24) 295–309.
    • Busogi, M. , Shin, D. (2017). Weighted affordance-based agent modeling and simulation in emergency evacuation. Saf. Sci , 96 (12): 209-227.
    • Chow, W. , (2011). Simulation of emergency evacuation in the arrival hall of a crowded airport. The Hong Kong Polytechnic University, 11 (1): 32-48.
    • Eng, L. , Aik, (2012). Simulating Evacuations with Obstacles. Journal of Applied Mathematics ,  8, (23): 23-34.
    • Fahy, R. , Proulxm, G. (2001). Toward Creating a Database on Delay Times to Start Evacuation and Walking Speeds for Use in Cvacuation Modelling. human Behavior in fire, 8 ,(6): 175-193.
    • Fang, J. , Tawil, E. (2016). Leader-follower model for agent based simulation. Saf. Sci, 83 (1): 209-227.
    • Georgoudas, I. , Sirakoulis, C. (2015). An anticipative crowd management system. IEEE Systems Journal, 5(1): 56-67.
    • Gerges, M. , Penn, S. , Moore, D. , Boothman, C. , & Liyanage, C. (2018). Multi-storey residential buildings. International Journal of Building Pathology. 22 (5): 25-38.
    • Glenn, C. , (2009). Introduction to the Futures Research Methods Series. Futures Research Methodology, 10 (3): 32-45
    • Ha, V. , Lykotrafitis, G. (2012). Agent-based modeling of a multi-room multi-floor building. Physica A: Statistical Mechanics and its Applications, 391 (8): 40-51.
    • Heliövaara, S. , Korhonen, T. (2012). Counter_ow model for agent-based simulation. Building Environ, 48 (8): 165-173.
    • Kia, g. , liamo, g.  (2022).  Adaptive multi-objective optimization for emergency evacuation at metro stations. Reliability Engineering & System Safety, 219(23):  65-37.
    • Manley, M. , Kim, Y. (2018). Modeling emergency evacuation of individuals with disabilities (exitus): An agent-based public decision support. Expert Syst, Appl, 39 ( 9): 8300-8311.
    • Neaupane, K. , Piantanakulchai, M. (2006). Analytic network process model for landslide hazard zonation, Engineering. 48 (85): 281–294.
    • Pluchino, S. , Tribulato, G. (2015). Agent-based model for pedestrians’ Evacuation after a blast integrated with a human behavior model. In Proc, 39 (9): 1506-1517.
    • Sharma, S. , Lohgaonkar, S. (2010). Simulation of agent behavior in a goal _nding application, in Proc. IEEE SoutheastCon (SoutheastCon), Concord, NC, 8 (2): 424-427.
    • Sheeba, A. , Jayaparvathy, R. (2019). Performance modeling of an intelligent emergency evacuation system in buildings on accidental fire occurrence. Safety Science. 74 (85): 196–205.
    • Shuchao, C. , Jialong, Q. Xiaolian, L. & Jie, Ni. (2020). Evacuation simulation considering the heterogeneity of pedestrian under terrorist attacks. International Journal of Disaster Risk Reduction, 79 (6): 56-69.
    • Slaughter, R. , (1993). future concepts. future, 3 (24): 289-314.
    • Stamatopoulou, I. , Sakellariou, I. (2012). agent-based behavior and simulation of crowd behavior in emergency evacuation. In2012 IEEE 24th International Conference on Tools with Artificial.
    • Wang, F. , Xu, X. (2021). Simulation Research on Fire Evacuation. Journal of Applied Mathematics, 1 (2): 122–130.
    • Xiangxia , Yanghui,   Hu. (2022). Simulation of building evacuation with different ratios of the elderly considering the influence of obstacle position. Physica A: Statistical Mechanics and its Applications, 604 (7): 87-103.
    • Xiaoxia, Y. , Rui, Z.  &   Yongxing,  L. (2022). Passenger Evacuation Path Planning in Subway Station Under Multiple Fires Based on Multiobjective Robust Optimization. IEEE Transactions on Intelligent Transportation Systems, 23 (6): 96-109.
    • Yi, W., Özdamar, W. (2018). A dynamic logistics coordination model for evacuation. European journal of operational research, 7 (8): 1177-1193.
    • Zali, N., F, Atrian. (2016). The development of regional tourism development scenarios based. Journal of Spatial managemen, 9 (8): 107-131.
    • Zhang, J., Song, W. (2008). Experiment and multi-grid modeling of evacuation. Physica A: Statistical Mechanics and its Applications, 387 (23): 5901-5909.
    • Zhu, K., Yang, Y & Shi, Q. (2016). Study on evacuation of pedestrians from a room with multi-obstacles considering the effect of aisles. Simulation Modelling Practice and Theory, 7 (8): 31- 69.

Files

Share

How to cite

Statistics