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Police patrol district design using agent-based simulation and GIS

机译:基于代理的仿真和GIS的警察巡逻区设计

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Police patrols play an important role in public safety. The patrol district design is an important factor affecting the patrol performances, such as average response time and workload variation. The redistricting procedure can be described as partitioning smaller geographical units into several larger districts with the constraints of contiguity and compactness. The size of the possible sample space is large and the corresponding graph-partitioning problem is NP-complete. In our approach, the patrol districting plans generated by a parameterized redistricting procedure are evaluated using an agent-based simulation model we implemented in Java Repast in a geographic information system (GIS) environment. The relationship between districting parameters and response variables is studied and better districting plans can be generated. After in-depth evaluations of these plans, we perform a Pareto analysis of the outputs from the simulation to find the non-dominated set of plans on each of the objectives. This paper also includes a case study for the police department of Charlottesville, VA, USA. Simulation results show that patrol performance can be improved compared with the current districting solution.
机译:警察巡逻在公共安全中起着重要作用。巡逻区设计是影响巡逻性能的重要因素,例如平均响应时间和工作量变化。重新划分过程可以描述为在连续性和紧凑性的约束下将较小的地理单元划分为几个较大的区域。可能的样本空间很大,并且相应的图分区问题是NP完全的。在我们的方法中,使用我们在Java Repast中在地理信息系统(GIS)环境中实现的基于代理的仿真模型,评估了由参数化重新划分程序生成的巡逻分区计划。研究了分区参数和响应变量之间的关系,可以生成更好的分区计划。在对这些计划进行深入评估之后,我们对模拟输出进行了帕累托分析,以找到每个目标上非主导的计划集。本文还包括针对美国弗吉尼亚州夏洛茨维尔市警察局的案例研究。仿真结果表明,与当前的分区解决方案相比,巡逻性能得以提高。

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