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Simulation-based optimization of emergency evacuation strategy in ultra-high-rise buildings

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Abstract

Emergency evacuation in high-rise buildings is a crucial problem. The evacuation strategy of using stairs and evacuation elevators should be optimized. In this paper, simulation-based optimization method is used to optimize the evacuation strategy of using stairs and elevators in high-rise buildings. The stair simulation is based on a cellular automata model, and several typical pedestrians’ walk preferences are considered in this model. In the simulation, evacuation elevators can arrive at the refuge floors, and the scheduling of the elevators is optimized based on the GA algorithm. The simulation-based optimization is designed as a two-level problem: The upper level is a strategy level; the lower level is an operation level. In the study case, the evacuation strategy of a 100-floor ultra-high-rise office building is optimized. We find that if evacuees follow the traditional stair evacuation strategy, the evacuation time is 42.6 min. After optimization, the evacuation time of optimal strategy by using both stairs and elevators is 25.1 min. Compared with the traditional stair evacuation strategy, the efficiency of evacuation is improved by 41.1%. It is also found that the merging behavior in stairwells will decrease the velocity of the pedestrian flow. Stairs are still the main egress, and evacuation elevators are an assistant egress during high-rise building evacuation.

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References

  • Abdelsalam HME, Bao HP (2006) A simulation-based optimization framework for product development cycle time reduction. IEEE Trans Eng Manag 53(1):69–85

    Article  Google Scholar 

  • Al-Aomar R (2006) Designing machine operating strategy with simulated annealing and Monte Carlo simulation. J Frankl Inst 343(4):372–388

    Article  Google Scholar 

  • Al-Dhaheri N, Jebali A, Diabat A (2016) A simulation-based Genetic Algorithm approach for the quay crane scheduling under uncertainty. Simul Model Pract Theory 66:122–138

    Article  Google Scholar 

  • Alrabghi A, Tiwari A (2013) A review of simulation-based optimisation in maintenance operations. In: 2013 UKSim 15th international conference on computer modelling and simulation 10–12 April 2013, Cambridge, IEEE, Piscataway, pp 353–358

  • Alrabghi A, Tiwari A (2015) State of the art in simulation-based optimisation for maintenance systems. Comput Ind Eng 82:167–182

    Article  Google Scholar 

  • Amaran S, Sahinidis NV, Sharda B et al (2014) Simulation optimization: a review of algorithms and applications. 4OR 12(4):301–333

    Article  Google Scholar 

  • Asano M, Iryo T, Kuwahara M (2010) Microscopic pedestrian simulation model combined with a tactical model for route choice behaviour. Transp Res Part C Emerg Technol 18(6):842–855

    Article  Google Scholar 

  • Delgarm N, Sajadi B, Kowsary F et al (2016) Multi-objective optimization of the building energy performance: a simulation-based approach by means of particle swarm optimization (PSO). Appl Energy 170:293–303

    Article  Google Scholar 

  • Ding Y, Yang L, Weng F et al (2015) Investigation of combined stairs elevators evacuation strategies for high rise buildings based on simulation. Simul Model Pract Theory 53:60–73

    Article  Google Scholar 

  • Duh JD, Brown DG (2007) Knowledge-informed Pareto simulated annealing for multi-objective spatial allocation. Comput Environ Urban Syst 31(3):253–281

    Article  Google Scholar 

  • Fu L, Luo J, Deng M et al (2012) Simulation of evacuation processes in a large classroom using an improved cellular automaton model for pedestrian dynamics. Procedia Eng 31:1066–1071

    Article  Google Scholar 

  • Galea ER, Hulse L, Day R et al (2010) The UK WTC 9/11 evacuation study: an overview of the methodologies employed and some preliminary analysis. In: Pedestrian and evacuation dynamics 2008. Springer, Berlin, pp 3–24

  • Georgoudas IG, Kyriakos P, Sirakoulis GC et al (2010) An FPGA implemented cellular automaton crowd evacuation model inspired by the electrostatic-induced potential fields. Microprocess Microsyst 34(7):285–300

    Article  Google Scholar 

  • Hao QY, Jiang R, Hu MB et al (2011) Pedestrian flow dynamics in a lattice gas model coupled with an evolutionary game. Phys Rev E 84(3):036107

    Article  Google Scholar 

  • He Q, Wang L, Liu B (2007) Parameter estimation for chaotic systems by particle swarm optimization. Chaos Solitons Fractals 34(2):654–661

    Article  Google Scholar 

  • Helbing D, Farkas I (2002) Simulation of pedestrian crowds in normal and evacuation situations. In: Schreckenberg M, Sharma SD (eds) Pedestrian and evacuation dynamics. Springer, Berlin, pp 21–58

    Google Scholar 

  • Helbing D, Molnar P (1995) Social force model for pedestrian dynamics. Phys Rev E 51(5):4282

    Article  Google Scholar 

  • Helbing D, Farkas IJ, Vicsek T (2000) Freezing by heating in a driven mesoscopic system. Phys Rev Lett 84(6):1240

    Article  Google Scholar 

  • Helbing D, Farkas IJ, Molnar P, Vicsek T (2002) Simulation of pedestrian crowds in normal and evacuation situations. Pedestr Evacuation Dyn 21(2):21–58

    Google Scholar 

  • Henderson LF (1971) The statistics of crowd fluids. Nature 229:381–383

    Article  Google Scholar 

  • Heyes E, Spearpoint M (2012) Lifts for evacuation-human behaviour considerations. Fire Mater 36(4):297–308

    Article  Google Scholar 

  • Hoogendoorn SP, Bovy PHL (2005) Pedestrian travel behavior modeling. Netw Spat Econ 5(2):193–216

    Article  Google Scholar 

  • Huo F, Song W, Lv W et al (2014) Analyzing pedestrian merging flow on a floor–stair interface using an extended lattice gas model. Simulation 90(5):501–510

    Article  Google Scholar 

  • Jacobs PHM, Verbraeck A, Mulder JBP (2005) Flight scheduling at KLM. In: Proceedings of the winter simulation conference, IEEE, p 8

  • Lovas GG (1994) Modeling and simulation of pedestrian traffic flow. Transp Res Part B Methodol 28(6):429–443

    Article  Google Scholar 

  • Lu WZ, Lo SM, Fang Z et al (2001) A preliminary investigation of airflow field in designated refuge floor. Build Environ 36(2):219–230

    Article  Google Scholar 

  • Ma J, Lo SM, Song WG (2012) Cellular automaton modeling approach for optimum ultra high-rise building evacuation design. Fire Saf J 54:57–66

    Article  Google Scholar 

  • Meijing G (2009) Simulation based optimization approaches for multi-echelon inventory control of supply China distribution networks. Doctoral dissertation, Northeastern University, China

  • Ning Ding, Hui Zhang, Tao Chen et al (2015) Stair evacuation simulation based on cellular automata considering evacuees’ walk preferences. Chin Phys B 24(6):687–693

    Google Scholar 

  • Paul RJ, Chanev TS (1998) Simulation optimisation using a genetic algorithm. Simul Pract Theory 6(6):601–611

    Article  Google Scholar 

  • Pelechano N, Malkawi A (2008) Evacuation simulation models: challenges in modeling high rise building evacuation with cellular automata approaches. Autom Constr 17(4):377–385

    Article  Google Scholar 

  • Peng YC, Chou CI (2011) Simulation of pedestrian flow through a “T” intersection: a multi-floor field cellular automata approach. Comput Phys Commun 182(1):205–208

    Article  Google Scholar 

  • Proulx G, Johnson P, Heyes E et al (2009) The use of elevators for egress: discussion panel. In: Proceedings of human behaviour in fire conference, pp 97–110

  • Reneke PA, Peacock RD, Hoskins BL (2013) Combined stairwell and elevator use during building evacuation. US Department of Commerce, National Institute of Standards and Technology, Gaithersburg

    Google Scholar 

  • Ronchi E, Reneke PA, Peacock RD (2014) A method for the analysis of behavioural uncertainty in evacuation modelling. Fire Technol 50:1545–1571

    Article  Google Scholar 

  • Santé I, García AM, Miranda D et al (2010) Cellular automata models for the simulation of real-world urban processes: a review and analysis. Landsc Urban Plan 96(2):108–122

    Article  Google Scholar 

  • Sun J, Zhao QC, Luh PB (2010) Optimization of group elevator scheduling with advance information. IEEE Trans Autom Sci Eng 7(2):352–363

    Article  Google Scholar 

  • Tampère C, Van Arem B, Hoogendoorn S (2003) Gas-kinetic traffic flow modeling including continuous driver behavior models. Transp Res Rec J Transp Res Board 1852:231–238

    Article  Google Scholar 

  • Tekin E, Sabuncuoglu I (2004) Simulation optimization: a comprehensive review on theory and applications. IIE Trans 36(11):1067–1081

    Article  Google Scholar 

  • Truong TH, Azadivar F (2003) Simulation optimization in manufacturing analysis: simulation based optimization for supply chain configuration design. In: Proceedings of the 35th conference on winter simulation: driving innovation. winter simulation conference, pp 1268–1275

  • Tsai SC, Fu SY (2014) Genetic-algorithm-based simulation optimization considering a single stochastic constraint. Eur J Oper Res 236(1):113–125

    Article  Google Scholar 

  • Wang JY, Weng WG, Zhang XL (2014) New insights into the crowd characteristics in Mina. J Stat Mech Theory Exp 2014:P11003

    Article  Google Scholar 

  • Was J (2005) Cellular automata model of pedestrian dynamics for normal and evacuation conditions. In: 5th international conference on intelligent systems design and applications (ISDA’05), IEEE, pp 154–159

  • Wąs J, Lubaś R (2014) Towards realistic and effective agent-based models of crowd dynamics. Neurocomputing 146:199–209

    Article  Google Scholar 

  • Yue H, Guan H, Zhang J et al (2010) Study on bi-direction pedestrian flow using cellular automata simulation. Physica A 389(3):527–539

    Article  Google Scholar 

  • Zhang XL, Weng WG, Yuan HY (2012) Empirical study of crowd behavior during a real mass event. J Stat Mech Theory Exp 2012(08):P08012

    Article  Google Scholar 

  • Zhang XL, Weng WG, Yuan HY, Chen JG (2013) Empirical study of a unidirectional dense crowd during a real mass event. Physica A 392:2781–2791

    Article  Google Scholar 

  • Zou N, Yeh ST, Chang GL et al (2005) Simulation-based emergency evacuation system for Ocean City, Maryland, during hurricanes. Transp Res Rec J Transp Res Board 1922:138–148

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by the Basic Research Program of People’s Public Security University of China (2016JKF01307), the National Natural Science Foundation of China (71373139, 91646201) and the 12th Five-Year Technology Support Program (2015BAK10B00). The authors appreciate the support for this paper by the Collaborative Innovation Center of Public Safety.

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Authors and Affiliations

  1. School of Criminal Investigation and Counterterror, People’s Public Security University of China, Beijing, China

    Ning Ding

  2. Institute of Public Safety Research, Tsinghua University, Beijing, China

    Hui Zhang & Tao Chen

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  1. Ning Ding
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  2. Hui Zhang
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  3. Tao Chen
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Correspondence to Ning Ding.

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Ding, N., Zhang, H. & Chen, T. Simulation-based optimization of emergency evacuation strategy in ultra-high-rise buildings. Nat Hazards 89, 1167–1184 (2017). https://doi.org/10.1007/s11069-017-3013-1

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