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An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model

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Abstract

Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (grant numbers 61876102, 61472232, 61272094 and 61603169).

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Authors and Affiliations

  1. School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China

    Yuan Zhao & Hong Liu

  2. Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, Jinan, 250014, China

    Yuan Zhao & Hong Liu

  3. Macau Institute of Systems Engineering, Macau University of Science and Technology, Macau, 999078, China

    Kaizhou Gao

Authors
  1. Yuan Zhao
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  2. Hong Liu
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  3. Kaizhou Gao
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Correspondence to Hong Liu.

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Appendix

Appendix

Table 9 Comparison among ABCs for the 30-dimensional cases
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Table 10 Comparison among ABCs for the 50-dimensional cases
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Zhao, Y., Liu, H. & Gao, K. An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model. Appl Intell 51, 100–123 (2021). https://doi.org/10.1007/s10489-020-01711-6

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