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

doi:10.1007/s10489-022-03975-6

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

2022-09-08

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Zhitong Ma

钟

钟竞辉 (Jinghui Zhong) *

DOI：10.1007/s10489-022-03975-6

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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.

Keywords:

Deployment of security guard

Differential evolution

Crowd simulation

Social force model

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

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