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An evolutionary framework for automatic security guards deployment in large public spaces

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Abstract

The deployment of security guards in large public spaces is a promising research topic with a wide range of applications. Existing methods are mainly based on manual design approaches, which are neither effective nor flexible enough for large-scale scenarios. To address this issue, this paper proposes an evolutionary framework to automatically generate the optimal deployment strategy of security guards in large public spaces. The proposed method includes a new metric for automatically evaluating deployment strategies, as well as an evolutionary solver based on differential evolution to optimize the deployment strategy automatically. To evaluate its effectiveness, the proposed evolutionary framework is tested on two synthetic scenarios with different characteristics and one real-world scenario. The results demonstrate that the proposed framework outperforms several commonly used strategies in terms of the response time of security guards.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 62076098), the Guangdong Natural Science Foundataion Research Team (Grant No. 2018B030312003), the GuangDong Basic and Applied Basic Research Foundation (Grant No. 2021A1515110072), and the research start-up funds of Guangdong Polytechnic Normal University (Grant No. 2021SDKYA130).

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Authors and Affiliations

  1. School of Computer Science and Engineering, South China University of Technology, No.382 Waihuan Dong Road, Guangzhou, 510006, Guangdong, China

    Zhitong Ma & Jinghui Zhong

  2. School of Computer Science, Guangdong Polytechnic Normal University, No.293 West Zhongshan Road, Guangzhou, 510665, Guangdong, China

    Wei-Li Liu

  3. School of Information Management, Sun Yat-Sen University, No.135 Xingang Road West Road, Guangzhou, 510275, Guangdong, China

    Wei-Jie Yu

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  1. Zhitong Ma
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  2. Jinghui Zhong
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Correspondence to Jinghui Zhong or Wei-Li Liu.

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Ma, Z., Zhong, J., Liu, WL. et al. An evolutionary framework for automatic security guards deployment in large public spaces. Appl Intell 53, 11586–11598 (2023). https://doi.org/10.1007/s10489-022-03975-6

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