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A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector

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  • Camacho-Collados, M.
  • Liberatore, F.
  • Angulo, J.M.

Abstract

The Police Districting Problem (PDP) concerns the efficient and effective design of patrol sectors in terms of performance attributes such as workload, response time, etc. A balanced definition of the patrol sector is desirable as it results in crime reduction and in better service. In this paper, a multi-criteria Police Districting Problem defined in collaboration with the Spanish National Police Corps is presented. This is the first model for the PDP that considers the attributes of area, risk, compactness, and mutual support. The decision-maker can specify his/her preferences on the attributes, on workload balance, and efficiency. The model is solved by means of a heuristic algorithm that is empirically tested on a case study of the Central District of Madrid. The solutions identified by the model are compared to patrol sector configurations currently in use and their quality is evaluated by public safety service coordinators. The model and the algorithm produce designs that significantly improve on the current ones.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:246:y:2015:i:2:p:674-684
    DOI: 10.1016/j.ejor.2015.05.023
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    Cited by:

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    3. Baghersad, Milad & Emadikhiav, Mohsen & Huang, C. Derrick & Behara, Ravi S., 2023. "Modularity maximization to design contiguous policy zones for pandemic response," European Journal of Operational Research, Elsevier, vol. 304(1), pages 99-112.
    4. Diglio, Antonio & Peiró, Juanjo & Piccolo, Carmela & Saldanha-da-Gama, Francisco, 2023. "Approximation schemes for districting problems with probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 307(1), pages 233-248.
    5. Han, Jialin & Hu, Yaoguang & Mao, Mingsong & Wan, Shuping, 2020. "A multi-objective districting problem applied to agricultural machinery maintenance service network," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1120-1130.
    6. Sebastián Moreno & Jordi Pereira & Wilfredo Yushimito, 2020. "A hybrid K-means and integer programming method for commercial territory design: a case study in meat distribution," Annals of Operations Research, Springer, vol. 286(1), pages 87-117, March.
    7. Liberatore, Federico & Camacho-Collados, Miguel & Quijano-Sánchez, Lara, 2023. "Towards social fairness in smart policing: Leveraging territorial, racial, and workload fairness in the police districting problem," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    8. Alsenafi, Abdulaziz & Barbaro, Alethea B.T., 2018. "A convection–diffusion model for gang territoriality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 765-786.
    9. Yuchen Luo & Bruce Golden & Rui Zhang, 2023. "The Hot Spot Coverage Patrol Problem: Formulations and Solution Approaches," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1286-1307, November.
    10. Antonio Diglio & Stefan Nickel & Francisco Saldanha-da-Gama, 2020. "Towards a stochastic programming modeling framework for districting," Annals of Operations Research, Springer, vol. 292(1), pages 249-285, September.
    11. Shixiang Zhu & He Wang & Yao Xie, 2022. "Data-Driven Optimization for Atlanta Police-Zone Design," Interfaces, INFORMS, vol. 52(5), pages 412-432, September.

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