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Modelling policing strategies for departments with limited resources

Published online by Cambridge University Press:  06 November 2015

ALEJANDRO CAMACHO ,
HYE RIN LINDSAY LEE  and
LAURA M. SMITH
ALEJANDRO CAMACHO
Affiliation:
California State University, Fullerton Department of Mathematics email: [email protected], [email protected]
HYE RIN LINDSAY LEE
Affiliation:
Case Western Reserve University Department of Mathematics, Applied Mathematics, and Statistics email: [email protected]
LAURA M. SMITH
Affiliation:
California State University, Fullerton Department of Mathematics email: [email protected], [email protected]
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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.

Keywords

Agent Based MethodsCrime ModelsHot SpotsPolicing Strategies
Type
Papers
Information
European Journal of Applied Mathematics , Volume 27 , Issue 3: Mathematical Modelling of Crime and Security , June 2016 , pp. 479 - 501
Copyright
Copyright © Cambridge University Press 2015 

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