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Data-Driven Optimization for Atlanta Police-Zone Design

Author

Listed:
  • Shixiang Zhu

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • He Wang

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Yao Xie

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

We present a data-driven optimization framework for redesigning police patrol zones in an urban environment. The objectives are to rebalance police workload along geographical areas and to reduce response time to emergency calls. We develop a stochastic model for police emergency response by integrating multiple data sources, including police incident reports, demographic surveys, and traffic data. Using this stochastic model, we optimize zone-redesign plans using mixed-integer linear programming. Our proposed design was implemented by the Atlanta Police Department in March 2019. By analyzing data before and after the zone redesign, we show that the new design has reduced the response time to high-priority 911 calls by 5.8% and the imbalance of police workload among Atlanta’s zones by 43%.

Suggested Citation

  • Shixiang Zhu & He Wang & Yao Xie, 2022. "Data-Driven Optimization for Atlanta Police-Zone Design," Interfaces, INFORMS, vol. 52(5), pages 412-432, September.
    • Handle: RePEc:inm:orinte:v:52:y:2022:i:5:p:412-432
    DOI: 10.1287/inte.2022.1122
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    References listed on IDEAS

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    1. Camacho-Collados, M. & Liberatore, F. & Angulo, J.M., 2015. "A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector," European Journal of Operational Research, Elsevier, vol. 246(2), pages 674-684.
    2. S. W. Hess & J. B. Weaver & H. J. Siegfeldt & J. N. Whelan & P. A. Zitlau, 1965. "Nonpartisan Political Redistricting by Computer," Operations Research, INFORMS, vol. 13(6), pages 998-1006, December.
    3. Mi Lim Lee & David Goldsman & Seong-Hee Kim & Kwok-Leung Tsui, 2014. "Spatiotemporal biosurveillance with spatial clusters: control limit approximation and impact of spatial correlation," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 813-827, August.
    4. Kevin Curtin & Karen Hayslett-McCall & Fang Qiu, 2010. "Determining Optimal Police Patrol Areas with Maximal Covering and Backup Covering Location Models," Networks and Spatial Economics, Springer, vol. 10(1), pages 125-145, March.
    5. Samuel E. Bodily, 1978. "Police Sector Design Incorporating Preferences of Interest Groups for Equality and Efficiency," Management Science, INFORMS, vol. 24(12), pages 1301-1313, August.
    6. R. S. Garfinkel & G. L. Nemhauser, 1970. "Optimal Political Districting by Implicit Enumeration Techniques," Management Science, INFORMS, vol. 16(8), pages 495-508, April.
    7. Jan M. Chaiken & Richard C. Larson, 1972. "Methods for Allocating Urban Emergency Units: A Survey," Management Science, INFORMS, vol. 19(4-Part-2), pages 110-130, December.
    8. Kenneth Chelst & James P. Jarvis, 1979. "Technical Note—Estimating the Probability Distribution of Travel Times for Urban Emergency Service Systems," Operations Research, INFORMS, vol. 27(1), pages 199-204, February.
    9. E. S. Levine & Jessica Tisch & Anthony Tasso & Michael Joy, 2017. "The New York City Police Department’s Domain Awareness System," Interfaces, INFORMS, vol. 47(1), pages 70-84, February.
    10. Linda V. Green & Peter J. Kolesar, 2004. "ANNIVERSARY ARTICLE: Improving Emergency Responsiveness with Management Science," Management Science, INFORMS, vol. 50(8), pages 1001-1014, August.
    11. F. Liberatore & M. Camacho-Collados, 2016. "A Comparison of Local Search Methods for the Multicriteria Police Districting Problem on Graph," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-13, March.
    12. GARFINKEL, Robert S. & NEMHAUSER, Geroge L., 1970. "Optimal political districting by implicit enumeration techniques," LIDAM Reprints CORE 54, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Anuj Mehrotra & Ellis L. Johnson & George L. Nemhauser, 1998. "An Optimization Based Heuristic for Political Districting," Management Science, INFORMS, vol. 44(8), pages 1100-1114, August.
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