Abstract
ABSTRACTIn police planning, a territory is often divided into several patrol districts with balanced workloads, in order to repress crime and provide better police service. Conventionally, in this districting problem, there is insufficient consideration of the impacts of street networks. In this study, we propose a street-network police districting problem (SNPDP) that explicitly uses streets as basic underlying units. This model defines the workload as a combination of different attributes and seeks an efficient and balanced design of districts. We also develop an efficient heuristic to generate high-quality districting plans in an acceptable time. The capability of the algorithm is demonstrated in comparison to an exact linear programming solver on simulated datasets. The SNPDP model is successfully implemented and tested in a case study in London, and the generated police districts have different characteristics that are consistent with the crime risk and land use distribution. Besides, we demonstrate that SNPDP is superior to an aggregation grid-based model regarding the solution quality. This model has the potential to generate street-based districts with balanced workloads for other districting problems, such as school districting and health care districting.
Highlights
Districting is the problem of grouping small geographic areas into larger and contiguous geographic clusters, in a way that the results meet the predefined planning criteria (Kalcsics 2015)
This is a novel approach to incorporating the street network structure and street-level predictive crime risk into the design of police districts
In comparison with solutions found by an exact solver (GUROBI), the GP–TS is capable of producing high-quality solutions quickly for the street-network police districting problem (SNPDP)
Summary
Districting is the problem of grouping small geographic areas into larger and contiguous geographic clusters, in a way that the results meet the predefined planning criteria (Kalcsics 2015). Districting problems have been motivated by and applied to a large number of fields, ranging from political districting of electoral areas (Vickrey 1961, Cirincione et al 2000, Bozkaya et al 2003), sales and service territory alignment (Hess and Samuels 1971, Blais et al 2003, Galvão et al 2006), health care districting (Thomas 1979), school districting (Clarke and Surkis 1968, Schoepfle and Church 1991, Caro et al 2004), to police patrol districting (Mitchell 1972, Curtin et al 2005). Some districts are overstaffed while others are understaffed, and the officers with excessive workload would become dissatisfied. For these reasons, some police departments would redesign the division boundaries after a certain period to equalise the workload (Kistler 2009)
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