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Modelling policing strategies for departments with limited resources

Published online by Cambridge University Press:  06 November 2015

ALEJANDRO CAMACHO
Affiliation:
California State University, Fullerton Department of Mathematics email: camacho@csu.fullerton.edu, lausmith@fullerton.edu
HYE RIN LINDSAY LEE
Affiliation:
Case Western Reserve University Department of Mathematics, Applied Mathematics, and Statistics email: hyerin.lee@case.edu
LAURA M. SMITH
Affiliation:
California State University, Fullerton Department of Mathematics email: camacho@csu.fullerton.edu, lausmith@fullerton.edu

Abstract

Crime prevention is a major goal of law-enforcement agencies. Often, these agencies have limited resources and officers available for patrolling and responding to calls. However, patrolling and police visibility can influence individuals to not perform criminal acts. Therefore, it is necessary for the police to optimize their patrolling strategies to deter the most crime. Previous studies have created agent-based models to simulate criminal and police agents interacting in a city, indicating a “cops on the dots” strategy as a viable method to mitigate large amounts of crime. Unfortunately, police departments cannot allocate all of the patrolling officers to seek out these hotspots, particularly since they are not immediately known. In large cities, it is often necessary to keep a few officers in different areas of the city, frequently divided up into beats. Officers need to respond to calls, possibly not of a criminal nature. Therefore, we modify models for policing to account for these factors. Through testing the policing strategies for various hotspot types and number of police agents, we found that the methods that performed the best varied greatly according to these factors.

Type
Papers
Copyright
Copyright © Cambridge University Press 2015 

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