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Determining Accurate Patrol Routes Using Genetic Algorithm and Ant Colony

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Abstract

Conventional street patrols by police have exhibited decreasing effectiveness and have become formalistic. However, these patrols play a significant role in preventing and stopping crime. In this study, precise patrol routes are developed using the ant colony shortest route algorithm on the basis of crime hotspots in urban areas (i.e., patrol points). As ant colony optimization can often converge to a local optimum, patrol points are reselected using the K-means algorithm and patrol routes are optimized via a genetic algorithm. As a result, accurate patrol routes are obtained.

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Funding

This study is partially supported by National first-class undergraduate major construction project, excellent innovation team of Philosophy and social sciences in Jiangsu Universities.

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Authors and Affiliations

  1. School of Information Technology, Nanjing Forest Police College, 210023, Nanjing, China

    Qiu Mingyue

  2. Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, 210023, Nanjing, China

    Zhang Xueying

Authors
  1. Qiu Mingyue
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  2. Zhang Xueying
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Correspondence to Qiu Mingyue.

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The authors declare that they have no conflicts of interest.

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Qiu Mingyue, Zhang Xueying Determining Accurate Patrol Routes Using Genetic Algorithm and Ant Colony. Aut. Control Comp. Sci. 57, 337–347 (2023). https://doi.org/10.3103/S0146411623040065

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  • DOI: https://doi.org/10.3103/S0146411623040065

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