Objectives

The Police Districting Problem concerns the definition of patrol districts that distribute police resources in a territory in such a way that high-risk areas receive more patrolling time than low-risk areas, according to a principle of territorial fairness. This results in patrolling configurations that are efficient and effective at controlling crime but that, at the same time, might exacerbate racial disparity in police stops and arrests. In this paper, an Equitable Police Districting Problem that combines crime-reduction effectiveness with racial fairness is proposed. The capability of this model in designing patrolling configurations that find a balance between territorial and racial fairness is assessed. Also, the trade-off between these two criteria is analyzed.

Methods

The Equitable Police Districting Problem is defined as a mixed-integer program. The objective function is formulated using Compromise Programming and Goal Programming. The model is validated on a real-world case study on the Central District of Madrid, Spain, and its solutions are compared to standard patrolling configurations currently used by the police.

Results

A trade-off between racial fairness and crime control is detected. However, the experiments show that including the proposed racial criterion in the optimization of patrol districts greatly improves racial fairness with limited detriment to the policing effectiveness. Also, the model produces solutions that dominate the patrolling configurations currently in use by the police.

Conclusions

The results show that the model successfully provides a quantitative evaluation of the trade-off between the criteria and is capable of defining patrolling configurations that are efficient in terms of both racial and territorial fairness.

中文翻译：

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警察分区问题中的平等：巡逻中的领土和种族公平平衡

目标

警察区划问题涉及对巡逻区的定义，这种巡逻区根据领土公平原则在一个领土上分配警察资源，以使高风险地区比低风险地区获得更多的巡逻时间。这导致巡逻结构在控制犯罪方面既有效又有效，但同时又可能加剧警察在制止和逮捕中的种族差异。本文提出了一个将减少犯罪的有效性与种族公平相结合的公平警察区划问题。评估了该模型在设计巡逻配置时能够在区域和种族公平之间寻求平衡的能力。同样，分析了这两个标准之间的权衡。

方法

公平警察区划问题定义为混合整数程序。使用折衷编程和目标编程来制定目标函数。该模型已在西班牙马德里中央区的实际案例研究中得到验证，并将其解决方案与警方目前使用的标准巡逻配置进行了比较。

结果

检测到种族公平与犯罪控制之间的权衡。然而，实验表明，在巡逻区的优化中包括拟议的种族标准，可以极大地改善种族公平性，而对治安效果的损害却有限。此外，该模型还产生了解决方案，该解决方案主导了警察当前正在使用的巡逻配置。

结论

结果表明，该模型成功地提供了标准之间的折衷的定量评估，并且能够定义在种族和领土公平方面均有效的巡逻配置。