Abstract
Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage scarce police resources and minimize emergency response times. The objective of this review paper is to discuss solution methods that can be used to solve the so-called police patrol routing problem (PPRP). The starting point of the review is the existing literature on the dynamic vehicle routing problem (DVRP). A keyword search resulted in 30 articles that focus on the DVRP with a link to police. Although the articles refer to policing, there is no specific focus on the PPRP; hence, there is a knowledge gap. A diversity of approaches is put forward ranging from more convenient solution methods such as a (hybrid) Genetic Algorithm (GA), linear programming and routing policies, to more complex Markov Decision Processes and Online Stochastic Combinatorial Optimization. Given the objectives, characteristics, advantages and limitations, the (hybrid) GA, routing policies and local search seem the most valuable solution methods for solving the PPRP.
Highlights
Since the 1990s, law enforcement has been increasingly influenced by the literature on the relationship between crime and place
A review of the PPRP in particular does not yet exist [11,13]. We address this and answer the following research question: “What algorithms or strategies exist to solve the police patrol routing problem as a dynamic vehicle routing problem?” This review qualitatively analyses articles on DVRPs with a specific focus on police
The solution methods that seem most convenient to address this PPRP based on this review are shown in Table 2. (Hybrid) Genetic Algorithms, routing policies and local search based on a network voronoi diagram are best suited to solve the PPRP, based on their characteristics, objectives, advantages and limitations (Table 2)
Summary
Since the 1990s, law enforcement has been increasingly influenced by the literature on the relationship between crime and place. Technological advances in hardware and software, e.g., the proliferation of computerised police information systems and more affordable Geographic Information Systems (GIS), are at the basis of this increased influence [1]. In research on routing strategies, similar technological advances led to the availability of real-time information at lower costs, which resulted in a major expansion of the existing solution methods for routing problems [5,6]. Police patrol routing strategies which incorporate the responsibilities of police officers on patrol are still missing [7] To address these deficiencies, this paper examines which algorithms can regulate effective police patrol routing, with a focus on overt or visible crime, i.e., crimes occurring in public places, which can be seen and heard by other people and can draw police attention. Overt crime is of interest to police officers—combating public nuisance is one of their duties, e.g., vandalism and loitering [8,9,10]
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