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

作者：Ma, Zhitong; Zhong, Jinghui^*; Liu, Wei-Li^*; Yu, Wei-Jie

来源：Applied Intelligence, 2023, 53(10): 11586-11598.

DOI：10.1007/s10489-022-03975-6

• Deployment of security guard
• Differential evolution
• Crowd simulation
• Social force model

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.

• 单位
  中山大学; 广东技术师范学院