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A Break from Tradition for the San Francisco Police: Patrol Officer Scheduling Using an Optimization-Based Decision Support System

Author

Listed:
  • Philip E. Taylor

    (McLaren College of Business, University of San Francisco, Ignatian Heights, San Francisco, California 94117)

  • Stephen J. Huxley

    (McLaren College of Business, University of San Francisco, Ignatian Heights, San Francisco, California 94117)

Abstract

The San Francisco Police Department (SFPD) recently implemented an optimization-based decision support system for deploying patrol officers. It forecasts hourly needs, schedules officers to maximize coverage, and allows fine tuning to meet human needs. The fine-tuning mode helps captains evaluate schedule changes and suggests alternatives. The system also evaluates policy options for strategic deployment. The integer search procedure generates solutions that make 25 percent more patrol units available in times of need, equivalent to adding 200 officers to the force or a savings of $11 million per year. Response times improved 20 percent, while revenues from traffic citations increased by $3 million per year.

Suggested Citation

  • Philip E. Taylor & Stephen J. Huxley, 1989. "A Break from Tradition for the San Francisco Police: Patrol Officer Scheduling Using an Optimization-Based Decision Support System," Interfaces, INFORMS, vol. 19(1), pages 4-24, February.
    • Handle: RePEc:inm:orinte:v:19:y:1989:i:1:p:4-24
    DOI: 10.1287/inte.19.1.4
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    Citations

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    Cited by:

    1. Sukanya Samanta & Goutam Sen & Soumya Kanti Ghosh, 2022. "A literature review on police patrolling problems," Annals of Operations Research, Springer, vol. 316(2), pages 1063-1106, September.
    2. Linda V. Green & Peter J. Kolesar & João Soares, 2001. "Improving the Sipp Approach for Staffing Service Systems That Have Cyclic Demands," Operations Research, INFORMS, vol. 49(4), pages 549-564, August.
    3. Gary M. Thompson, 1997. "Labor staffing and scheduling models for controlling service levels," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(8), pages 719-740, December.
    4. Michael J. Brusco & Larry W. Jacobs, 2000. "Optimal Models for Meal-Break and Start-Time Flexibility in Continuous Tour Scheduling," Management Science, INFORMS, vol. 46(12), pages 1630-1641, December.
    5. Michael J. Brusco & Larry W. Jacobs, 1998. "Personnel Tour Scheduling When Starting-Time Restrictions Are Present," Management Science, INFORMS, vol. 44(4), pages 534-547, April.
    6. Brusco, Michael J. & Jacobs, Larry W., 1995. "Cost analysis of alternative formulations for personnel scheduling in continuously operating organizations," European Journal of Operational Research, Elsevier, vol. 86(2), pages 249-261, October.
    7. Castillo, Ignacio & Joro, Tarja & Li, Yong Yue, 2009. "Workforce scheduling with multiple objectives," European Journal of Operational Research, Elsevier, vol. 196(1), pages 162-170, July.
    8. Robert M. Saltzman & Jennifer L. Meyer, 2004. "A Consulting Firm Uses Constraint Programming to Plan Personnel-Review Meetings," Interfaces, INFORMS, vol. 34(2), pages 106-112, April.
    9. Peters, Emmanuel & de Matta, Renato & Boe, Warren, 2007. "Short-term work scheduling with job assignment flexibility for a multi-fleet transport system," European Journal of Operational Research, Elsevier, vol. 180(1), pages 82-98, July.
    10. de Matta, Renato & Peters, Emmanuel, 2009. "Developing work schedules for an inter-city transit system with multiple driver types and fleet types," European Journal of Operational Research, Elsevier, vol. 192(3), pages 852-865, February.
    11. Easton, F. F. & Rossin, D. F., 1997. "Overtime schedules for full-time service workers," Omega, Elsevier, vol. 25(3), pages 285-299, June.
    12. Jiun-Yan Shiau & Ming-Kung Huang & Chu-Yi Huang, 2020. "A Hybrid Personnel Scheduling Model for Staff Rostering Problems," Mathematics, MDPI, vol. 8(10), pages 1-20, October.
    13. Easton, Fred F. & Mansour, Nashat, 1999. "A distributed genetic algorithm for deterministic and stochastic labor scheduling problems," European Journal of Operational Research, Elsevier, vol. 118(3), pages 505-523, November.
    14. Casado Yusta, S. & Pacheco Bonrostro, J., 2003. "Estudio comparativo de diferentes estrategias metaheurísticas para la resolución del labor scheduling problem./Analisys of different methauristas for solving labor scheduling," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 21, pages 537-554, December.
    15. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    16. Young-Chae Hong & Amy Cohn & Stephen Gorga & Edmond O’Brien & William Pozehl & Jennifer Zank, 2019. "Using Optimization Techniques and Multidisciplinary Collaboration to Solve a Challenging Real-World Residency Scheduling Problem," Interfaces, INFORMS, vol. 49(3), pages 201-212, May.
    17. N C Simpson & P G Hancock, 2009. "Fifty years of operational research and emergency response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 126-139, May.
    18. Hoong Chuin Lau & Zhi Yuan & Aldy Gunawan, 2016. "Patrol scheduling in urban rail network," Annals of Operations Research, Springer, vol. 239(1), pages 317-342, April.
    19. Garza Escalante, Enrique F. & Paniagua Fernandez, L. Fernando, 2016. "Preparing transitions in public services: Payoff dimension, value estimation, schedule and budget computation," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 36-46.
    20. S Casado & M Laguna & J Pacheco, 2005. "Heuristical labour scheduling to optimize airport passenger flows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 649-658, June.
    21. Brusco, Michael J. & Jacobs, Larry W., 2001. "Starting-time decisions in labor tour scheduling: An experimental analysis and case study," European Journal of Operational Research, Elsevier, vol. 131(3), pages 459-475, June.

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