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 数据分析与知识发现  2018, Vol. 2 Issue (10): 37-45    DOI: 10.11925/infotech.2096-3467.2018.0769
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Optimizing Anti-terrorist Policing with Queueing Theory
Zhongyi Liu,Chenwang Hu(),Kun Tan,Yan Gao
School of Management, People’s Public Security University of China, Beijing 100038, China
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【目的】应用排队论模型, 优化反恐警力配置策略, 提高反恐效率和效果。【方法】M/M/1/∞和M/M/N/∞两类排队模型的基础上, 构建两种反恐警力优化配置模型, 分别求解最优警力配置方案, 通过算例对两种警力优化配置模型进行比较分析。【结果】基于M/M/N/∞排队模型的反恐警力配置模型在反恐警力配置效率和恐怖袭击案件处置效率方面更具优势。【局限】由于实际恐怖袭击案件数据和警力数据获取受限, 未进行实际数据的验证。【结论】应用排队论模型可以实现反恐警力资源的有效配置, 尤其应用M/M/N/∞模型更具优势, 可以有效提高反恐警力配置效率和恐怖袭击案件处置效率。

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Abstract

[Objective] This paper optimizes the deployment of anti-terrorist police resources based on the queueing theory, aiming to improve the effectiveness of counterterrorism actions. [Methods] First, we proposed two optimal anti-terrorist policing strategies based on the M/M/1/∞ and M/M/N/∞ queueing models. Then, we compared the performance of the two models with simulation cases on four factors. [Results] We found that the M/M/N/∞ model had better performance. [Limitations] We did not examine the proposed model with real world anti-terrorism and policing data. [Conclusions] The M/M/N/∞ queueing model could help us create better anti-terrorist policing strategies.

Key wordsQueueing Theory    Anti-Terrorist    Optimization of Police Resources

 引用本文: 刘忠轶,胡晨望,谭坤,高岩. 基于排队论的反恐警力优化配置策略研究*[J]. 数据分析与知识发现, 2018, 2(10): 37-45. Zhongyi Liu,Chenwang Hu,Kun Tan,Yan Gao. Optimizing Anti-terrorist Policing with Queueing Theory. Data Analysis and Knowledge Discovery, DOI：10.11925/infotech.2096-3467.2018.0769. 链接本文: http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2018.0769
 图1  M/M/1/∞反恐排队模型 图2  M/M/N/∞反恐排队模型 表1  M/M/1/∞反恐排队模型中c1对n*和Wq的影响 表2  M/M/1/∞反恐排队模型中c2对n*和Wq的影响 表3  M/M/N/∞反恐排队模型中c3对N*和Wq的影响 表4  M/M/N/∞反恐排队模型中c2对N*和Wq的影响
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