Optimizing Evacuation Strategies in Mountain Communities to Mitigate Geohazards Risk: A Hybrid Simulation Framework

Abstract

Evacuation strategies play a crucial role in mitigating human casualties from geohazards. While evacuation simulations have been widely used to investigate crowd behavior in response to disasters such as fires and earthquakes, their application to investigating crowd behavior in response to geohazards in mountainous areas has been limited. In this study, a framework was developed for simulating and optimizing evacuation strategies in response to geohazards in mountainous areas that considers the behavioral characteristics of residents. First, a simulation scenario is constructed by analyzing satellite imagery of the region of interest to identify and classify various geographic features. Characteristic parameters are then embedded into a hybrid algorithm that combines the ant colony system algorithm with a social force model to simulate realistic evacuation scenarios that reflect crowd behavior during emergencies. Based on the results of numerical simulations, the existing configuration of shelter locations are optimized to address the chaos and congestion resulting from crowd behavior. As a case study, the proposed framework was applied to constructing geohazard scenarios for a community in the Longmen Mountains area of China and conducting numerical simulations to optimize the evacuation strategy. The results show that the optimized strategies helped facilitate the safe evacuation of residents. The proposed framework represents a multidisciplinary approach to developing evacuation strategies in response to geohazards in mountainous areas while considering crowd behavior. This research has practical implications for guiding public evacuations in mountain communities under the backdrop of geohazards and provides innovative solutions for crowd evacuations in similar scenarios.

Keywords

Ant colony system / Crowd evacuation / Geohazards / Mountain communities / Social force model

References

[1] AlbiG, CristianiE, PareschiL, PeriD. Mathematical models and methods for crowd dynamics control. Crowd Dynamics, 2020, 2: 159-197.

[2] BlueVJ, AdlerJL. Cellular automata microsimulation for modeling bi-directional pedestrian walkways. Transportation Research Part B: Methodological, 2001, 35(3): 293-312.

[3] Chai, L., Y. Han, Z. Han, J. Wei, and Y. Zhao. 2021. Differences in disaster preparedness between urban and rural communities in China. International Journal of Disaster Risk Reduction 53: Article 102020.

[4] ChalmetLG, FrancisRL, SaundersPB. Network models for building evacuation. Management Science, 1982, 28(1): 86-105.

[5] ChenX, ZhanFB. Agent-based modelling and simulation of urban evacuation: Relative effectiveness of simultaneous and staged evacuation strategies. Journal of the Operational Research Society, 2008, 59(1): 25-33.

[6] Dorigo, M., and G. Di Caro. 1999. Ant colony optimization: A new meta-heuristic. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, 6–9 July 1999, Washington, DC, USA.

[7] DorigoM, GambardellaLM. Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 53-66.

[8] DruryJ. The role of social identity processes in mass emergency behaviour: An integrative review. European Review of Social Psychology, 2018, 29(1): 38-81.

[9] FrischU, HasslacherB, PomeauY. Lattice-gas automata for the Navier-Stokes equation. Physical Review Letters, 1986, 56(14): 1505-1508.

[10] GuzzettiF, ArdizzoneF, CardinaliM, RossiM, ValigiD. Landslide volumes and landslide mobilization rates in Umbria, Central Italy. Earth and Planetary Science Letters, 2009, 279(3–4): 222-229.

[11] GwynneS, GaleaER, OwenM, LawrencePJ, FilippidisL. A review of the methodologies used in the computer simulation of evacuation from the built environment. Building and Environment, 1999, 34(6): 741-749.

[12] HelbingD. A fluid-dynamic model for the movement of pedestrians. ArXiv (Cornell University), 1992, 6(5): 391-415

[13] HelbingD, MolnárP. Social force model for pedestrian dynamics. Physical Review E, 1995, 51(5): 4282-4286.

[14] HelbingD, FarkasI, VicsekT. Simulating dynamical features of escape panic. Nature, 2000, 407(6803): 487-490.

[15] HendersonLF. On the fluid mechanics of human crowd motion. Transportation Research, 1974, 8(6): 509-515.

[16] HoogendoornSP, BovyPHL. Pedestrian route-choice and activity scheduling theory and models. Transportation Research Part B: Methodological, 2004, 38(2): 169-190.

[17] HughesRL. A continuum theory for the flow of pedestrians. Transportation Research Part B: Methodological, 2002, 36(6): 507-735.

[18] KapucuN. Collaborative emergency management: Better community organising, better public preparedness and response. Disasters, 2008, 32(2): 239-262.

[19] KingB. Spatialising livelihoods: Resource access and livelihood spaces in South Africa. Transactions of the Institute of British Geographers, 2011, 36(2): 297-313.

[20] Li, S., L. Peng, X. Wang, K. Huang, and J. Tang. 2023. Do geohazards inhibit urban expansion at the regional scale? Evidence from a counterfactual analysis in Southwest China. Cities 142: Article 104558.

[21] LiS, PengL, WuW, HuangZ, LiuY. Does labor out-migration affect the sustainability of disaster mitigation? Insight from the social-ecological system perspective. Sustainable Development, 2023, 32(1): 1-14.

[22] Li, X., C. Wang, M.A. Kassem, and K.N. Ali. 2024. Emergency evacuation of urban underground commercial street based on BIM approach. Ain Shams Engineering Journal 15(4): Article 102633.

[23] Liang, S., L. Peng, G. Yang, H. Zhang, and Y. Jin. 2025. Modeling residents’ long-term adaptation to geohazards in mountainous regions using agent-based models and Bayesian networks. International Journal of Disaster Risk Reduction 119: Article 105279.

[24] LindellMK, PerryRW. The protective action decision model: Theoretical modifications and additional evidence. Risk Analysis, 2011, 32(4): 616-632.

[25] Ministry of Natural Resources of the People’s Republic of China. 2024. 2023 China natural resources bulletin. Beijing: Ministry of Natural Resources. https://ecs.mnr.gov.cn/dhj/gk/gbytj/202403/P020240304369959267727.pdf. Accessed 16 May 2024 (in Chinese).

[26] PengL, TanJ. Identifying neighborhood effects on geohazard adaptation in mountainous rural areas of China: A spatial econometric model. International Journal of Disaster Risk Science, 2023, 14(6): 919-931.

[27] Peng, L., K. Huang, H. Zhang, and W. Sun. 2024. Exploring the impacts of urbanization on vegetation growth from the perspective of urban expansion patterns and maturity: A case study on 40 large cities in China. Sustainable Cities and Society 115: Article 105841.

[28] PengL, LiS, TanJ, ZhangX. Peer effects affect the adaptation behaviour of rural residents to geohazards in China: A new policy pathway. Climate Policy, 2024, 25: 1-17

[29] ReynoldsC, BennettEL. A distributed behavioral model. ACM SIGGRAPH Computer Graphics, 1987, 21(4): 25-34.

[30] Rodrı́guez, C.E., J.J. Bommer, and R.J. Chandler. 1999. Earthquake-induced landslides: 1980–1997. Soil Dynamics and Earthquake Engineering 18(5): 325–346.

[31] Ronchi, E., and D. Nilsson. 2013. Fire evacuation in high-rise buildings: A review of human behaviour and modelling research. Fire Science Reviews 2(1): Article 7.

[32] ShiwakotiN, SarviM, RoseG, BurdM. Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions. Transportation Research Part B: Methodological, 2011, 45(9): 1433-1449.

[33] SimeJD. Affiliative behaviour during escape to building exits. Journal of Environmental Psychology, 1983, 3(1): 21-41.

[34] SlovicP. Perception of risk. Science, 1987, 236(4799): 280-285.

[35] Solnon, C., and D. Bridge. 2006. An ant colony optimization meta-heuristic for subset selection problems. In System engineering using particle swarm optimization, ed. N. Nedjah, and L. de Macedo Mourelle, 3–25. New York: Nova Science Publishers.

[36] Sutton, J., and K. Tierney. 2006. Disaster preparedness: Concepts, guidance, and research. Natural Hazards Center, Institute of Behavioral Science, University of Colorado Bolder. https://www.researchgate.net/publication/266479116_Disaster_Preparedness_Concepts_Guidance_and_Research. Accessed 18 Sept 2025.

[37] Tan, J., L. Peng, W. Wu, H. Zhang, and C. Tang. 2024. Exploring the evolution and trade-off within a socio-ecological system in Karst regions: A case study of Huanjiang County, China. Geography and Sustainability 6(3): Article 100256.

[38] TreuilleA, CooperS, PopovićZ. Continuum crowds. ACM Transactions on Graphics, 2006, 25(3): 1160-1168.

[39] Wang, X., L. Peng, K. Huang, and W. Deng. 2022. Identifying the influence of disaster education on the risk perception of rural residents in geohazard-prone areas: A propensity score-matched study. International Journal of Disaster Risk Reduction 71: Article 102795.

[40] Wei, Y., L. Jin, M. Xu, S. Pan, Y. Xu, and Y. Zhang. 2020. Instructions for planning emergency shelters and open spaces in China: Lessons from global experiences and expertise. International Journal of Disaster Risk Reduction 51: Article 101813.

[41] Yang, Y., J. Yin, D. Wang, Y. Liu, Y. Lu, W. Zhang, and S. Xu. 2023. ABM-based emergency evacuation modelling during urban pluvial floods: A “7.20” pluvial flood event study in Zhengzhou, Henan Province. Science China Earth Sciences 66(2): 282–291.

[42] YinJ, YangY, YuD, LinN, WilbyR, LaneS, SunB, BrickerJ, et al.. Strategic storm flood evacuation planning for large coastal cities enables more effective transfer of elderly populations. Nature Water, 2024, 2(3): 274-284.

[43] YuanJP, FangZ, WangYC, LoSM, WangP. Integrated network approach of evacuation simulation for large complex buildings. Fire Safety Journal, 2009, 44(2): 266-275.

[44] Zeng, Y., B. Di, W. He, S. Wu, J. Li, A. Nienkötter, O. Li, Q. Peng, and X. Meng. 2024. Searching for emergency shelters in rural China: A systematic review of policies and literature. International Journal of Disaster Risk Reduction 115: Article 105017.

[45] Zhang, Z., X. Yao, Z. Xing, and X. Zhou. 2024. Simulation on passenger evacuation of metro train fire in the tunnel. Chaos, Solitons & Fractals 187: Article 115429.

[46] ZhengX, ZhongT, LiuM. Modeling crowd evacuation of a building based on seven methodological approaches. Building and Environment, 2009, 44(3): 437-445.

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